From 1163801bb4b70f5b14f77146b936e7fcb822d9a6 Mon Sep 17 00:00:00 2001 From: etiennebacher Date: Tue, 17 Feb 2026 18:39:10 +0100 Subject: [PATCH 1/5] init --- tests/testthat/_snaps/estimate_contrasts.md | 688 ------ .../plot-facet/plot-interaction-facets-1.svg | 130 - .../plot-facet/plot-interaction-facets-10.svg | 257 -- .../plot-facet/plot-interaction-facets-2.svg | 113 - .../plot-facet/plot-interaction-facets-3.svg | 708 ------ .../plot-facet/plot-interaction-facets-4.svg | 566 ----- .../plot-facet/plot-interaction-facets-5.svg | 439 ---- .../plot-facet/plot-interaction-facets-6.svg | 833 ------- .../plot-facet/plot-interaction-facets-7.svg | 2114 ----------------- .../plot-facet/plot-interaction-facets-8.svg | 728 ------ .../plot-facet/plot-interaction-facets-9.svg | 566 ----- .../plot-interaction-facets-cat-1.svg | 298 --- .../plot-interaction-facets-cat-2.svg | 528 ---- .../plot-interaction-facets-cat-3.svg | 489 ---- .../plot-interaction-facets-cat-4emmeans.svg | 289 --- 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zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(827) | p - -------------------------------------------------------------------- - mid | low | -0.09 | 0.34 | [-0.76, 0.58] | -0.25 | 0.802 - high | low | 0.61 | 0.43 | [-0.24, 1.45] | 1.40 | 0.162 - high | mid | 0.69 | 0.36 | [-0.02, 1.40] | 1.92 | 0.055 - - Variable predicted: neg_c_7 - Predictors contrasted: c172code - Predictors averaged: e16sex, c161sex - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(fit, c("c161sex", "c172code"), backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(825) | p - ------------------------------------------------------------------------------- - Male, mid | Male, low | 0.29 | 0.71 | [-1.10, 1.68] | 0.41 | 0.684 - Male, high | Male, low | 0.69 | 0.83 | [-0.95, 2.32] | 0.82 | 0.410 - Female, low | Male, low | 1.05 | 0.69 | [-0.31, 2.40] | 1.51 | 0.131 - Female, mid | Male, low | 0.85 | 0.64 | [-0.40, 2.10] | 1.33 | 0.183 - Female, high | Male, low | 1.65 | 0.71 | [ 0.24, 3.05] | 2.30 | 0.022 - Male, high | Male, mid | 0.40 | 0.68 | [-0.94, 1.73] | 0.59 | 0.558 - Female, low | Male, mid | 0.76 | 0.50 | [-0.22, 1.73] | 1.52 | 0.129 - Female, mid | Male, mid | 0.56 | 0.42 | [-0.26, 1.38] | 1.35 | 0.178 - Female, high | Male, mid | 1.36 | 0.53 | [ 0.32, 2.39] | 2.58 | 0.010 - Female, low | Male, high | 0.36 | 0.66 | [-0.95, 1.66] | 0.54 | 0.589 - Female, mid | Male, high | 0.16 | 0.61 | [-1.03, 1.35] | 0.27 | 0.789 - Female, high | Male, high | 0.96 | 0.69 | [-0.39, 2.30] | 1.40 | 0.163 - Female, mid | Female, low | -0.20 | 0.39 | [-0.96, 0.57] | -0.51 | 0.613 - Female, high | Female, low | 0.60 | 0.51 | [-0.39, 1.59] | 1.18 | 0.236 - Female, high | Female, mid | 0.80 | 0.43 | [-0.04, 1.63] | 1.87 | 0.061 - - Variable predicted: neg_c_7 - Predictors contrasted: c161sex, c172code - Predictors averaged: e16sex - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(fit, "c161sex", "c172code", backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | c172code | Difference | SE | 95% CI | t(825) | p - ------------------------------------------------------------------------------- - Female | Male | low | 1.05 | 0.69 | [-0.31, 2.40] | 1.51 | 0.131 - Female | Male | mid | 0.56 | 0.42 | [-0.26, 1.38] | 1.35 | 0.178 - Female | Male | high | 0.96 | 0.69 | [-0.39, 2.30] | 1.40 | 0.163 - - Variable predicted: neg_c_7 - Predictors contrasted: c161sex - Predictors averaged: e16sex - p-values are uncorrected. - ---- - - Code - print(estimate_slopes(fit, "barthtot", backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Estimated Marginal Effects - - Slope | SE | 95% CI | t(810) | p - ----------------------------------------------- - -0.05 | 0.00 | [-0.06, -0.05] | -12.77 | < .001 - - Marginal effects estimated for barthtot - Type of slope was dY/dX - ---- - - Code - print(estimate_slopes(fit, "barthtot", by = "c172code", backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Estimated Marginal Effects - - c172code | Slope | SE | 95% CI | t(808) | p - ---------------------------------------------------------- - low | -0.06 | 0.01 | [-0.08, -0.05] | -7.08 | < .001 - mid | -0.05 | 0.01 | [-0.06, -0.04] | -9.82 | < .001 - high | -0.05 | 0.01 | [-0.07, -0.03] | -4.51 | < .001 - - Marginal effects estimated for barthtot - Type of slope was dY/dX - ---- - - Code - print(estimate_contrasts(fit, "barthtot", "c172code", backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(808) | p - -------------------------------------------------------------------- - mid | low | 0.01 | 0.01 | [-0.01, 0.03] | 1.17 | 0.243 - high | low | 0.02 | 0.01 | [-0.01, 0.04] | 1.10 | 0.271 - high | mid | 0.00 | 0.01 | [-0.02, 0.03] | 0.27 | 0.786 - - Variable predicted: neg_c_7 - Predictors contrasted: barthtot - Predictors averaged: e16sex, barthtot (65) - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(fit, "barthtot", c("c172code", "e16sex"), backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(803) | p - ------------------------------------------------------------------------------- - low, female | low, male | -0.01 | 0.02 | [-0.04, 0.03] | -0.35 | 0.729 - mid, male | low, male | -0.01 | 0.02 | [-0.04, 0.02] | -0.46 | 0.648 - mid, female | low, male | 0.02 | 0.01 | [-0.01, 0.05] | 1.24 | 0.217 - high, male | low, male | 0.00 | 0.02 | [-0.05, 0.04] | -0.16 | 0.876 - high, female | low, male | 0.02 | 0.02 | [-0.01, 0.06] | 1.19 | 0.236 - mid, male | low, female | 0.00 | 0.02 | [-0.03, 0.03] | -0.08 | 0.940 - mid, female | low, female | 0.02 | 0.01 | [ 0.00, 0.05] | 1.76 | 0.079 - high, male | low, female | 0.00 | 0.02 | [-0.04, 0.05] | 0.12 | 0.908 - high, female | low, female | 0.03 | 0.02 | [-0.01, 0.06] | 1.58 | 0.115 - mid, female | mid, male | 0.03 | 0.01 | [ 0.00, 0.05] | 2.24 | 0.026 - high, male | mid, male | 0.00 | 0.02 | [-0.04, 0.05] | 0.18 | 0.859 - high, female | mid, male | 0.03 | 0.02 | [ 0.00, 0.06] | 1.83 | 0.068 - high, male | mid, female | -0.02 | 0.02 | [-0.06, 0.02] | -1.08 | 0.280 - high, female | mid, female | 0.00 | 0.01 | [-0.02, 0.03] | 0.26 | 0.792 - high, female | high, male | 0.03 | 0.02 | [-0.02, 0.07] | 1.11 | 0.269 - - Variable predicted: neg_c_7 - Predictors contrasted: barthtot - Predictors averaged: barthtot (65) - p-values are uncorrected. - -# estimate_contrasts - simple contrasts and with - in levels works - - Code - print(estimate_contrasts(model, "Species", backend = "marginaleffects"), - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(146) | p - ---------------------------------------------------------------------------- - versicolor | setosa | 1.46 | 0.11 | [1.24, 1.68] | 13.01 | < .001 - virginica | setosa | 1.95 | 0.10 | [1.75, 2.14] | 19.47 | < .001 - virginica | versicolor | 0.49 | 0.09 | [0.31, 0.67] | 5.41 | < .001 - - Variable predicted: Sepal.Length - Predictors contrasted: Species - Predictors averaged: Sepal.Width (3.1) - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(m, c("time", "coffee"), backend = "marginaleffects"), - zap_small = TRUE, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(113) | p - --------------------------------------------------------------------------------------------- - morning, control | morning, coffee | -5.78 | 1.99 | [-9.73, -1.83] | -2.90 | 0.004 - noon, coffee | morning, coffee | -1.93 | 1.99 | [-5.88, 2.02] | -0.97 | 0.336 - noon, control | morning, coffee | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 - afternoon, coffee | morning, coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 - afternoon, control | morning, coffee | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 - noon, coffee | morning, control | 3.86 | 1.99 | [-0.09, 7.81] | 1.93 | 0.056 - noon, control | morning, control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 - afternoon, coffee | morning, control | 7.71 | 1.99 | [ 3.76, 11.66] | 3.87 | < .001 - afternoon, control | morning, control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 - noon, control | noon, coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 - afternoon, coffee | noon, coffee | 3.86 | 1.99 | [-0.09, 7.81] | 1.93 | 0.056 - afternoon, control | noon, coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 - afternoon, coffee | noon, control | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 - afternoon, control | noon, control | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 - afternoon, control | afternoon, coffee | -1.93 | 1.99 | [-5.88, 2.02] | -0.97 | 0.336 - - Variable predicted: alertness - Predictors contrasted: time, coffee - Predictors averaged: sex - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(m, contrast = "time", by = "coffee", backend = "marginaleffects"), - zap_small = TRUE, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | coffee | Difference | SE | 95% CI | t(113) | p - ----------------------------------------------------------------------------------- - noon | morning | coffee | -1.93 | 1.99 | [-5.88, 2.02] | -0.97 | 0.336 - afternoon | morning | coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 - afternoon | noon | coffee | 3.86 | 1.99 | [-0.09, 7.81] | 1.93 | 0.056 - noon | morning | control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 - afternoon | morning | control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 - afternoon | noon | control | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 - - Variable predicted: alertness - Predictors contrasted: time - Predictors averaged: sex - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model, contrast = c("mined", "spp"), backend = "marginaleffects"), - zap_small = TRUE, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | z | p - ----------------------------------------------------------------------------- - yes, PR | yes, GP | 0.06 | 0.05 | [-0.04, 0.16] | 1.10 | 0.271 - yes, DM | yes, GP | 0.32 | 0.11 | [ 0.10, 0.54] | 2.89 | 0.004 - yes, EC-A | yes, GP | 0.04 | 0.05 | [-0.05, 0.13] | 0.80 | 0.421 - yes, EC-L | yes, GP | 0.17 | 0.08 | [ 0.02, 0.32] | 2.19 | 0.028 - yes, DES-L | yes, GP | 0.43 | 0.14 | [ 0.17, 0.70] | 3.19 | 0.001 - yes, DF | yes, GP | 0.43 | 0.14 | [ 0.17, 0.70] | 3.19 | 0.001 - no, GP | yes, GP | 2.59 | 0.55 | [ 1.50, 3.67] | 4.67 | < .001 - no, PR | yes, GP | 0.51 | 0.16 | [ 0.20, 0.82] | 3.21 | 0.001 - no, DM | yes, GP | 2.86 | 0.61 | [ 1.68, 4.05] | 4.73 | < .001 - no, EC-A | yes, GP | 1.10 | 0.27 | [ 0.57, 1.64] | 4.03 | < .001 - no, EC-L | yes, GP | 4.67 | 0.94 | [ 2.82, 6.52] | 4.95 | < .001 - no, DES-L | yes, GP | 4.62 | 0.93 | [ 2.79, 6.45] | 4.95 | < .001 - no, DF | yes, GP | 2.24 | 0.49 | [ 1.28, 3.20] | 4.58 | < .001 - yes, DM | yes, PR | 0.26 | 0.11 | [ 0.05, 0.48] | 2.43 | 0.015 - yes, EC-A | yes, PR | -0.02 | 0.06 | [-0.13, 0.09] | -0.33 | 0.740 - yes, EC-L | yes, PR | 0.11 | 0.08 | [-0.04, 0.27] | 1.43 | 0.154 - yes, DES-L | yes, PR | 0.38 | 0.13 | [ 0.12, 0.64] | 2.86 | 0.004 - yes, DF | yes, PR | 0.38 | 0.13 | [ 0.12, 0.64] | 2.86 | 0.004 - no, GP | yes, PR | 2.53 | 0.56 | [ 1.44, 3.62] | 4.54 | < .001 - no, PR | yes, PR | 0.45 | 0.16 | [ 0.13, 0.77] | 2.75 | 0.006 - no, DM | yes, PR | 2.80 | 0.61 | [ 1.61, 4.00] | 4.61 | < .001 - no, EC-A | yes, PR | 1.05 | 0.28 | [ 0.50, 1.59] | 3.76 | < .001 - no, EC-L | yes, PR | 4.61 | 0.95 | [ 2.76, 6.47] | 4.87 | < .001 - no, DES-L | yes, PR | 4.56 | 0.94 | [ 2.73, 6.40] | 4.87 | < .001 - no, DF | yes, PR | 2.18 | 0.49 | [ 1.22, 3.15] | 4.44 | < .001 - yes, EC-A | yes, DM | -0.28 | 0.11 | [-0.50, -0.07] | -2.59 | 0.010 - yes, EC-L | yes, DM | -0.15 | 0.11 | [-0.36, 0.06] | -1.39 | 0.164 - yes, DES-L | yes, DM | 0.11 | 0.13 | [-0.14, 0.36] | 0.89 | 0.375 - yes, DF | yes, DM | 0.11 | 0.13 | [-0.14, 0.36] | 0.89 | 0.375 - no, GP | yes, DM | 2.27 | 0.58 | [ 1.14, 3.40] | 3.93 | < .001 - no, PR | yes, DM | 0.19 | 0.20 | [-0.21, 0.58] | 0.93 | 0.352 - no, DM | yes, DM | 2.54 | 0.63 | [ 1.31, 3.77] | 4.04 | < .001 - no, EC-A | yes, DM | 0.78 | 0.31 | [ 0.18, 1.38] | 2.56 | 0.011 - no, EC-L | yes, DM | 4.35 | 0.96 | [ 2.46, 6.24] | 4.51 | < .001 - no, DES-L | yes, DM | 4.30 | 0.95 | [ 2.43, 6.17] | 4.51 | < .001 - no, DF | yes, DM | 1.92 | 0.51 | [ 0.91, 2.93] | 3.74 | < .001 - yes, EC-L | yes, EC-A | 0.13 | 0.08 | [-0.02, 0.29] | 1.68 | 0.093 - yes, DES-L | yes, EC-A | 0.40 | 0.13 | [ 0.14, 0.66] | 2.97 | 0.003 - yes, DF | yes, EC-A | 0.40 | 0.13 | [ 0.14, 0.66] | 2.97 | 0.003 - no, GP | yes, EC-A | 2.55 | 0.56 | [ 1.46, 3.64] | 4.58 | < .001 - no, PR | yes, EC-A | 0.47 | 0.16 | [ 0.15, 0.79] | 2.90 | 0.004 - no, DM | yes, EC-A | 2.82 | 0.61 | [ 1.63, 4.01] | 4.65 | < .001 - no, EC-A | yes, EC-A | 1.06 | 0.28 | [ 0.52, 1.61] | 3.85 | < .001 - no, EC-L | yes, EC-A | 4.63 | 0.95 | [ 2.78, 6.48] | 4.90 | < .001 - no, DES-L | yes, EC-A | 4.58 | 0.94 | [ 2.75, 6.42] | 4.90 | < .001 - no, DF | yes, EC-A | 2.20 | 0.49 | [ 1.24, 3.17] | 4.49 | < .001 - yes, DES-L | yes, EC-L | 0.26 | 0.13 | [ 0.02, 0.51] | 2.08 | 0.037 - yes, DF | yes, EC-L | 0.26 | 0.13 | [ 0.02, 0.51] | 2.08 | 0.037 - no, GP | yes, EC-L | 2.42 | 0.57 | [ 1.31, 3.53] | 4.28 | < .001 - no, PR | yes, EC-L | 0.34 | 0.18 | [-0.01, 0.69] | 1.89 | 0.058 - no, DM | yes, EC-L | 2.69 | 0.62 | [ 1.48, 3.90] | 4.37 | < .001 - no, EC-A | yes, EC-L | 0.93 | 0.29 | [ 0.37, 1.50] | 3.23 | 0.001 - no, EC-L | yes, EC-L | 4.50 | 0.95 | [ 2.63, 6.37] | 4.72 | < .001 - no, DES-L | yes, EC-L | 4.45 | 0.94 | [ 2.60, 6.30] | 4.71 | < .001 - no, DF | yes, EC-L | 2.07 | 0.50 | [ 1.09, 3.05] | 4.14 | < .001 - yes, DF | yes, DES-L | 0.00 | 0.13 | [-0.26, 0.26] | 0.00 | > .999 - no, GP | yes, DES-L | 2.15 | 0.59 | [ 1.00, 3.31] | 3.67 | < .001 - no, PR | yes, DES-L | 0.07 | 0.22 | [-0.36, 0.50] | 0.33 | 0.738 - no, DM | yes, DES-L | 2.43 | 0.64 | [ 1.18, 3.68] | 3.81 | < .001 - no, EC-A | yes, DES-L | 0.67 | 0.32 | [ 0.04, 1.29] | 2.09 | 0.037 - no, EC-L | yes, DES-L | 4.24 | 0.97 | [ 2.33, 6.14] | 4.36 | < .001 - no, DES-L | yes, DES-L | 4.19 | 0.96 | [ 2.30, 6.07] | 4.35 | < .001 - no, DF | yes, DES-L | 1.81 | 0.52 | [ 0.78, 2.83] | 3.45 | < .001 - no, GP | yes, DF | 2.15 | 0.59 | [ 1.00, 3.31] | 3.67 | < .001 - no, PR | yes, DF | 0.07 | 0.22 | [-0.36, 0.50] | 0.33 | 0.738 - no, DM | yes, DF | 2.43 | 0.64 | [ 1.18, 3.68] | 3.81 | < .001 - no, EC-A | yes, DF | 0.67 | 0.32 | [ 0.04, 1.29] | 2.09 | 0.037 - no, EC-L | yes, DF | 4.24 | 0.97 | [ 2.33, 6.14] | 4.36 | < .001 - no, DES-L | yes, DF | 4.19 | 0.96 | [ 2.30, 6.07] | 4.35 | < .001 - no, DF | yes, DF | 1.81 | 0.52 | [ 0.78, 2.83] | 3.45 | < .001 - no, PR | no, GP | -2.08 | 0.48 | [-3.02, -1.14] | -4.35 | < .001 - no, DM | no, GP | 0.27 | 0.37 | [-0.46, 1.00] | 0.73 | 0.466 - no, EC-A | no, GP | -1.49 | 0.41 | [-2.29, -0.68] | -3.61 | < .001 - no, EC-L | no, GP | 2.08 | 0.58 | [ 0.95, 3.21] | 3.61 | < .001 - no, DES-L | no, GP | 2.03 | 0.57 | [ 0.92, 3.15] | 3.57 | < .001 - no, DF | no, GP | -0.35 | 0.35 | [-1.04, 0.35] | -0.98 | 0.328 - no, DM | no, PR | 2.35 | 0.53 | [ 1.32, 3.39] | 4.47 | < .001 - no, EC-A | no, PR | 0.59 | 0.23 | [ 0.14, 1.05] | 2.56 | 0.011 - no, EC-L | no, PR | 4.16 | 0.86 | [ 2.49, 5.84] | 4.87 | < .001 - no, DES-L | no, PR | 4.11 | 0.85 | [ 2.45, 5.77] | 4.86 | < .001 - no, DF | no, PR | 1.73 | 0.42 | [ 0.92, 2.55] | 4.15 | < .001 - no, EC-A | no, DM | -1.76 | 0.46 | [-2.65, -0.87] | -3.86 | < .001 - no, EC-L | no, DM | 1.81 | 0.55 | [ 0.73, 2.89] | 3.29 | < .001 - no, DES-L | no, DM | 1.76 | 0.54 | [ 0.70, 2.82] | 3.24 | 0.001 - no, DF | no, DM | -0.62 | 0.38 | [-1.36, 0.12] | -1.65 | 0.100 - no, EC-L | no, EC-A | 3.57 | 0.77 | [ 2.07, 5.07] | 4.66 | < .001 - no, DES-L | no, EC-A | 3.52 | 0.76 | [ 2.03, 5.00] | 4.65 | < .001 - no, DF | no, EC-A | 1.14 | 0.36 | [ 0.43, 1.85] | 3.16 | 0.002 - no, DES-L | no, EC-L | -0.05 | 0.48 | [-0.99, 0.89] | -0.10 | 0.918 - no, DF | no, EC-L | -2.43 | 0.61 | [-3.63, -1.22] | -3.95 | < .001 - no, DF | no, DES-L | -2.38 | 0.61 | [-3.57, -1.19] | -3.92 | < .001 - - Variable predicted: count - Predictors contrasted: mined, spp - Predictors averaged: cover (8.7e-11), site - p-values are uncorrected. - Contrasts are on the response-scale. - ---- - - Code - print(estimate_contrasts(model, contrast = "mined", by = "spp", backend = "marginaleffects"), - zap_small = TRUE, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | spp | Difference | SE | 95% CI | z | p - -------------------------------------------------------------------------- - no | yes | GP | 2.59 | 0.55 | [1.50, 3.67] | 4.67 | < .001 - no | yes | PR | 0.45 | 0.16 | [0.13, 0.77] | 2.75 | 0.006 - no | yes | DM | 2.54 | 0.63 | [1.31, 3.77] | 4.04 | < .001 - no | yes | EC-A | 1.06 | 0.28 | [0.52, 1.61] | 3.85 | < .001 - no | yes | EC-L | 4.50 | 0.95 | [2.63, 6.37] | 4.72 | < .001 - no | yes | DES-L | 4.19 | 0.96 | [2.30, 6.07] | 4.35 | < .001 - no | yes | DF | 1.81 | 0.52 | [0.78, 2.83] | 3.45 | < .001 - - Variable predicted: count - Predictors contrasted: mined - Predictors averaged: cover (8.7e-11), site - p-values are uncorrected. - Contrasts are on the response-scale. - -# estimate_contrasts - examples from docs work as intendec - - Code - print(estimate_contrasts(model, contrast = "Petal.Width", by = "Species"), - zap_small = TRUE, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(144) | p - ---------------------------------------------------------------------------- - versicolor | setosa | 0.22 | 0.46 | [-0.70, 1.13] | 0.47 | 0.640 - virginica | setosa | -0.21 | 0.44 | [-1.07, 0.66] | -0.47 | 0.638 - virginica | versicolor | -0.42 | 0.27 | [-0.95, 0.11] | -1.58 | 0.116 - - Variable predicted: Sepal.Width - Predictors contrasted: Petal.Width - Predictors averaged: Petal.Width (1.2) - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model, contrast = c("Species", "Petal.Width"), length = 2), - zap_small = TRUE, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(144) | p - ---------------------------------------------------------------------------------------- - setosa, 2.5 | setosa, 0.1 | 2.01 | 0.98 | [ 0.08, 3.94] | 2.06 | 0.041 - versicolor, 0.1 | setosa, 0.1 | -1.83 | 0.28 | [-2.38, -1.28] | -6.55 | < .001 - versicolor, 2.5 | setosa, 0.1 | 0.70 | 0.27 | [ 0.17, 1.23] | 2.61 | 0.010 - virginica, 0.1 | setosa, 0.1 | -1.55 | 0.31 | [-2.17, -0.93] | -4.95 | < .001 - virginica, 2.5 | setosa, 0.1 | -0.03 | 0.11 | [-0.25, 0.19] | -0.29 | 0.773 - versicolor, 0.1 | setosa, 2.5 | -3.84 | 0.96 | [-5.73, -1.95] | -4.01 | < .001 - versicolor, 2.5 | setosa, 2.5 | -1.31 | 0.95 | [-3.19, 0.58] | -1.37 | 0.172 - virginica, 0.1 | setosa, 2.5 | -3.56 | 0.97 | [-5.47, -1.65] | -3.68 | < .001 - virginica, 2.5 | setosa, 2.5 | -2.04 | 0.92 | [-3.86, -0.22] | -2.21 | 0.028 - versicolor, 2.5 | versicolor, 0.1 | 2.53 | 0.52 | [ 1.50, 3.56] | 4.86 | < .001 - virginica, 0.1 | versicolor, 0.1 | 0.28 | 0.41 | [-0.52, 1.08] | 0.69 | 0.492 - virginica, 2.5 | versicolor, 0.1 | 1.80 | 0.28 | [ 1.24, 2.35] | 6.35 | < .001 - virginica, 0.1 | versicolor, 2.5 | -2.25 | 0.40 | [-3.04, -1.46] | -5.64 | < .001 - virginica, 2.5 | versicolor, 2.5 | -0.73 | 0.27 | [-1.27, -0.20] | -2.70 | 0.008 - virginica, 2.5 | virginica, 0.1 | 1.52 | 0.37 | [ 0.77, 2.26] | 4.04 | < .001 - - Variable predicted: Sepal.Width - Predictors contrasted: Species, Petal.Width - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model, contrast = c("Species", "Petal.Width=c(1, 2)")), - zap_small = TRUE, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(144) | p - ------------------------------------------------------------------------------------ - setosa, 2 | setosa, 1 | 0.84 | 0.41 | [ 0.03, 1.64] | 2.06 | 0.041 - versicolor, 1 | setosa, 1 | -1.63 | 0.32 | [-2.27, -1.00] | -5.09 | < .001 - versicolor, 2 | setosa, 1 | -0.58 | 0.35 | [-1.26, 0.10] | -1.68 | 0.096 - virginica, 1 | setosa, 1 | -1.73 | 0.35 | [-2.43, -1.04] | -4.93 | < .001 - virginica, 2 | setosa, 1 | -1.10 | 0.31 | [-1.72, -0.48] | -3.52 | < .001 - versicolor, 1 | setosa, 2 | -2.47 | 0.72 | [-3.89, -1.05] | -3.43 | < .001 - versicolor, 2 | setosa, 2 | -1.42 | 0.73 | [-2.86, 0.03] | -1.94 | 0.055 - virginica, 1 | setosa, 2 | -2.57 | 0.73 | [-4.02, -1.12] | -3.50 | < .001 - virginica, 2 | setosa, 2 | -1.94 | 0.72 | [-3.35, -0.52] | -2.71 | 0.008 - versicolor, 2 | versicolor, 1 | 1.05 | 0.22 | [ 0.62, 1.48] | 4.86 | < .001 - virginica, 1 | versicolor, 1 | -0.10 | 0.19 | [-0.47, 0.27] | -0.54 | 0.589 - virginica, 2 | versicolor, 1 | 0.53 | 0.09 | [ 0.35, 0.71] | 5.72 | < .001 - virginica, 1 | versicolor, 2 | -1.15 | 0.23 | [-1.60, -0.71] | -5.13 | < .001 - virginica, 2 | versicolor, 2 | -0.52 | 0.16 | [-0.84, -0.21] | -3.31 | 0.001 - virginica, 2 | virginica, 1 | 0.63 | 0.16 | [ 0.32, 0.94] | 4.04 | < .001 - - Variable predicted: Sepal.Width - Predictors contrasted: Species, Petal.Width=c(1, 2) - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model, by = "Petal.Width", length = 4), zap_small = TRUE, - table_width = Inf) - Message - We selected `contrast=c("Species")`. - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Petal.Width | Difference | SE | 95% CI | t(144) | p - -------------------------------------------------------------------------------------------- - versicolor | setosa | 0.10 | -1.83 | 0.28 | [-2.38, -1.28] | -6.55 | < .001 - virginica | setosa | 0.10 | -1.55 | 0.31 | [-2.17, -0.93] | -4.95 | < .001 - virginica | versicolor | 0.10 | 0.28 | 0.41 | [-0.52, 1.08] | 0.69 | 0.492 - versicolor | setosa | 0.90 | -1.65 | 0.29 | [-2.22, -1.08] | -5.74 | < .001 - virginica | setosa | 0.90 | -1.71 | 0.32 | [-2.35, -1.07] | -5.28 | < .001 - virginica | versicolor | 0.90 | -0.06 | 0.21 | [-0.47, 0.35] | -0.28 | 0.780 - versicolor | setosa | 1.70 | -1.48 | 0.60 | [-2.67, -0.29] | -2.47 | 0.015 - virginica | setosa | 1.70 | -1.88 | 0.60 | [-3.06, -0.70] | -3.14 | 0.002 - virginica | versicolor | 1.70 | -0.40 | 0.11 | [-0.62, -0.17] | -3.50 | < .001 - versicolor | setosa | 2.50 | -1.31 | 0.95 | [-3.19, 0.58] | -1.37 | 0.172 - virginica | setosa | 2.50 | -2.04 | 0.92 | [-3.86, -0.22] | -2.21 | 0.028 - virginica | versicolor | 2.50 | -0.73 | 0.27 | [-1.27, -0.20] | -2.70 | 0.008 - - Variable predicted: Sepal.Width - Predictors contrasted: Species - p-values are uncorrected. - -# estimate_contrasts - test all combinations of contrast and by, with filtering - - Code - print(estimate_contrasts(model2, c("grp", "time", "x")), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(992) | p - -------------------------------------------------------------------------------------- - control, 1, b | control, 1, a | 0.15 | 0.13 | [-0.10, 0.40] | 1.20 | 0.231 - control, 2, a | control, 1, a | 0.03 | 0.13 | [-0.23, 0.28] | 0.19 | 0.847 - control, 2, b | control, 1, a | 0.09 | 0.13 | [-0.16, 0.34] | 0.73 | 0.465 - treatment, 1, a | control, 1, a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 - treatment, 1, b | control, 1, a | -0.03 | 0.13 | [-0.28, 0.22] | -0.22 | 0.824 - treatment, 2, a | control, 1, a | 0.02 | 0.13 | [-0.23, 0.27] | 0.19 | 0.850 - treatment, 2, b | control, 1, a | 0.05 | 0.12 | [-0.19, 0.28] | 0.37 | 0.712 - control, 2, a | control, 1, b | -0.12 | 0.13 | [-0.38, 0.13] | -0.97 | 0.332 - control, 2, b | control, 1, b | -0.06 | 0.12 | [-0.30, 0.19] | -0.46 | 0.648 - treatment, 1, a | control, 1, b | 0.04 | 0.13 | [-0.20, 0.29] | 0.34 | 0.730 - treatment, 1, b | control, 1, b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 - treatment, 2, a | control, 1, b | -0.13 | 0.12 | [-0.37, 0.12] | -1.02 | 0.307 - treatment, 2, b | control, 1, b | -0.10 | 0.12 | [-0.34, 0.13] | -0.89 | 0.376 - control, 2, b | control, 2, a | 0.07 | 0.13 | [-0.19, 0.32] | 0.52 | 0.604 - treatment, 1, a | control, 2, a | 0.17 | 0.13 | [-0.09, 0.43] | 1.26 | 0.207 - treatment, 1, b | control, 2, a | -0.05 | 0.13 | [-0.31, 0.20] | -0.41 | 0.680 - treatment, 2, a | control, 2, a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 - treatment, 2, b | control, 2, a | 0.02 | 0.13 | [-0.23, 0.27] | 0.16 | 0.876 - treatment, 1, a | control, 2, b | 0.10 | 0.13 | [-0.15, 0.35] | 0.78 | 0.437 - treatment, 1, b | control, 2, b | -0.12 | 0.13 | [-0.37, 0.12] | -0.97 | 0.333 - treatment, 2, a | control, 2, b | -0.07 | 0.13 | [-0.32, 0.18] | -0.55 | 0.582 - treatment, 2, b | control, 2, b | -0.05 | 0.12 | [-0.29, 0.19] | -0.40 | 0.691 - treatment, 1, b | treatment, 1, a | -0.22 | 0.13 | [-0.47, 0.03] | -1.73 | 0.083 - treatment, 2, a | treatment, 1, a | -0.17 | 0.13 | [-0.42, 0.08] | -1.32 | 0.187 - treatment, 2, b | treatment, 1, a | -0.15 | 0.12 | [-0.39, 0.09] | -1.20 | 0.230 - treatment, 2, a | treatment, 1, b | 0.05 | 0.12 | [-0.19, 0.30] | 0.42 | 0.676 - treatment, 2, b | treatment, 1, b | 0.07 | 0.12 | [-0.16, 0.31] | 0.61 | 0.541 - treatment, 2, b | treatment, 2, a | 0.02 | 0.12 | [-0.21, 0.26] | 0.18 | 0.861 - - Variable predicted: score - Predictors contrasted: grp, time, x - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, c("grp", "time"), by = "x"), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | x | Difference | SE | 95% CI | t(992) | p - ------------------------------------------------------------------------------------ - control, 2 | control, 1 | a | 0.03 | 0.13 | [-0.23, 0.28] | 0.19 | 0.847 - treatment, 1 | control, 1 | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 - treatment, 2 | control, 1 | a | 0.02 | 0.13 | [-0.23, 0.27] | 0.19 | 0.850 - treatment, 1 | control, 2 | a | 0.17 | 0.13 | [-0.09, 0.43] | 1.26 | 0.207 - treatment, 2 | control, 2 | a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 - treatment, 2 | treatment, 1 | a | -0.17 | 0.13 | [-0.42, 0.08] | -1.32 | 0.187 - control, 2 | control, 1 | b | -0.06 | 0.12 | [-0.30, 0.19] | -0.46 | 0.648 - treatment, 1 | control, 1 | b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 - treatment, 2 | control, 1 | b | -0.10 | 0.12 | [-0.34, 0.13] | -0.89 | 0.376 - treatment, 1 | control, 2 | b | -0.12 | 0.13 | [-0.37, 0.12] | -0.97 | 0.333 - treatment, 2 | control, 2 | b | -0.05 | 0.12 | [-0.29, 0.19] | -0.40 | 0.691 - treatment, 2 | treatment, 1 | b | 0.07 | 0.12 | [-0.16, 0.31] | 0.61 | 0.541 - - Variable predicted: score - Predictors contrasted: grp, time - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, "grp", by = c("time", "x")), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | time | x | Difference | SE | 95% CI | t(992) | p - ----------------------------------------------------------------------------------- - treatment | control | 1 | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 - treatment | control | 2 | a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 - treatment | control | 1 | b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 - treatment | control | 2 | b | -0.05 | 0.12 | [-0.29, 0.19] | -0.40 | 0.691 - - Variable predicted: score - Predictors contrasted: grp - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, "grp", by = "time"), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | time | Difference | SE | 95% CI | t(992) | p - ------------------------------------------------------------------------------- - treatment | control | 1 | 0.01 | 0.09 | [-0.17, 0.18] | 0.09 | 0.931 - treatment | control | 2 | -0.02 | 0.09 | [-0.20, 0.15] | -0.28 | 0.780 - - Variable predicted: score - Predictors contrasted: grp - Predictors averaged: x - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, c("grp", "time", "x='a'")), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(992) | p - -------------------------------------------------------------------------------- - control, 2 | control, 1 | 0.03 | 0.13 | [-0.23, 0.28] | 0.19 | 0.847 - treatment, 1 | control, 1 | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 - treatment, 2 | control, 1 | 0.02 | 0.13 | [-0.23, 0.27] | 0.19 | 0.850 - treatment, 1 | control, 2 | 0.17 | 0.13 | [-0.09, 0.43] | 1.26 | 0.207 - treatment, 2 | control, 2 | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 - treatment, 2 | treatment, 1 | -0.17 | 0.13 | [-0.42, 0.08] | -1.32 | 0.187 - - Variable predicted: score - Predictors contrasted: grp, time, x='a' - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, c("grp", "time=1"), by = "x"), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | x | Difference | SE | 95% CI | t(992) | p - ---------------------------------------------------------------------------- - treatment | control | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 - treatment | control | b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 - - Variable predicted: score - Predictors contrasted: grp, time=1 - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, "grp", by = c("time", "x='a'")), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | time | x | Difference | SE | 95% CI | t(992) | p - ----------------------------------------------------------------------------------- - treatment | control | 1 | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 - treatment | control | 2 | a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 - - Variable predicted: score - Predictors contrasted: grp - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, "time=c(1,2)", by = "grp"), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | grp | Difference | SE | 95% CI | t(994) | p - -------------------------------------------------------------------------------- - 2 | 1 | control | 0.14 | 0.11 | [-0.08, 0.36] | 1.24 | 0.216 - 2 | 1 | treatment | -0.07 | 0.11 | [-0.28, 0.14] | -0.63 | 0.529 - - Variable predicted: score - Predictors contrasted: time=c(1,2) - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(model2, c("grp", "time=2")), zap_small = TRUE, - table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(994) | p - ------------------------------------------------------------------------ - treatment | control | -0.15 | 0.11 | [-0.36, 0.05] | -1.47 | 0.143 - - Variable predicted: score - Predictors contrasted: grp, time=2 - p-values are uncorrected. - -# estimate_contrast, slopes with emmeans - - Code - print(out, table_width = Inf) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | 95% CI | p - ---------------------------------------------------------- - 0, 0.725 | 0, -2.012 | 1.12 | [0.37, 3.43] | 0.839 - 0, 3.463 | 0, -2.012 | 1.26 | [0.14, 11.76] | 0.839 - 1, -2.012 | 0, -2.012 | 1.00 | [0.35, 2.82] | 0.999 - 1, 0.725 | 0, -2.012 | 1.12 | [0.23, 5.43] | 0.887 - 1, 3.463 | 0, -2.012 | 1.26 | [0.10, 15.76] | 0.858 - 0, 3.463 | 0, 0.725 | 1.12 | [0.37, 3.43] | 0.839 - 1, -2.012 | 0, 0.725 | 0.89 | [0.20, 3.87] | 0.877 - 1, 0.725 | 0, 0.725 | 1.00 | [0.35, 2.82] | 0.999 - 1, 3.463 | 0, 0.725 | 1.12 | [0.23, 5.43] | 0.887 - 1, -2.012 | 0, 3.463 | 0.79 | [0.07, 8.71] | 0.849 - 1, 0.725 | 0, 3.463 | 0.89 | [0.20, 3.87] | 0.877 - 1, 3.463 | 0, 3.463 | 1.00 | [0.35, 2.82] | 0.999 - 1, 0.725 | 1, -2.012 | 1.12 | [0.37, 3.43] | 0.839 - 1, 3.463 | 1, -2.012 | 1.26 | [0.14, 11.76] | 0.839 - 1, 3.463 | 1, 0.725 | 1.12 | [0.37, 3.43] | 0.839 - - Variable predicted: outcome - Predictors contrasted: var_binom, var_cont - p-values are uncorrected. - Contrasts are on the link-scale. - diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-1.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-1.svg deleted file mode 100644 index a240b7a4b..000000000 --- a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-1.svg +++ /dev/null @@ -1,130 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Male - - - - - - - - - - -Female - - - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 -5 -10 -15 - - - -average number of hours of care per week -Mean of Negative impact with 7 items - -carer's level of education - - - - - - - - - -low level of education -intermediate level of education -high level of education -plot-interaction-facets-1 - - diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-10.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-10.svg deleted file mode 100644 index 1dad556c1..000000000 --- a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-10.svg +++ /dev/null @@ -1,257 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Male - - - - - - - - - - -Female - - - - - - - - - - -low level of education - - - - - - - - - - -intermediate level of education - - - - - - - - - - -high level of education - - - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 --10 -0 -10 -20 -30 -40 - - - - - - --10 -0 -10 -20 -30 -40 - - - - - - --10 -0 -10 -20 -30 -40 - - - - - - -average number of hours of care per week -Mean of Negative impact with 7 items - -elder's gender - - - - - - -male -female -plot-interaction-facets-10 - - diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-2.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-2.svg deleted file mode 100644 index f161d681f..000000000 --- a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-2.svg +++ /dev/null @@ -1,113 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -10 -12 -14 -16 -18 - - - - - - - - - -0 -50 -100 -150 -average number of hours of care per week -Mean of Negative impact with 7 items - -barthtot - - - - - - - - - - -0 -25 -50 -75 -100 - -carer's level of education - - - - - - -low level of education -intermediate level of education -high level of education -plot-interaction-facets-2 - - diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-3.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-3.svg deleted file mode 100644 index f44989580..000000000 --- a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-3.svg +++ /dev/null @@ -1,708 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 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-plot-interaction-facets-3 - - diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-4.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-4.svg deleted file mode 100644 index 3cfd5ace9..000000000 --- a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-4.svg +++ /dev/null @@ -1,566 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -0 - - - - - - - - - - -11.111 - - - - - - - - - - -22.222 - - - - - - - - - - -33.333 - - - - - - - - - - -44.444 - - - - - - - - - - -55.556 - - - - - - - - - - -66.667 - - - - - - - - - - -77.778 - - - - - - - - - - -88.889 - - - - - - - - - - -100 - - - - - - - - - - -Male - - - - - - - - - - -Female - - - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 - - - - -0 -50 -100 -150 -7.5 -10.0 -12.5 -15.0 -17.5 - - - - - -7.5 -10.0 -12.5 -15.0 -17.5 - - - - - -average number of hours of care per week -Mean of Negative impact with 7 items - -barthtot - - - - - - - - - - -0 -25 -50 -75 -100 - -carer's level of education - - - - - - -low level of education -intermediate level of education -high level of education -plot-interaction-facets-4 - - diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-5.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-5.svg deleted file mode 100644 index 214a47dc3..000000000 --- a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-5.svg +++ /dev/null @@ -1,439 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Male - - - - - - - - - - -Female - - - - - - - - - - -low level of education - - - - - - - - - - -intermediate level of education - - - - - - - - - - -high level of education - - - - - - -0 -50 -100 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- - - - - - - - - - - - - - -5 -6 -7 -8 - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Mean of Sepal.Length -plot-means-showdata-2 - - diff --git a/tests/testthat/_snaps/plot/plot-means-showdata-3.svg b/tests/testthat/_snaps/plot/plot-means-showdata-3.svg deleted file mode 100644 index 2f5a5d224..000000000 --- a/tests/testthat/_snaps/plot/plot-means-showdata-3.svg +++ /dev/null @@ -1,238 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 -8 - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Mean of Sepal.Length - -Species - - - - - - - - - - - - -setosa -versicolor -virginica -plot-means-showdata-3 - - diff --git a/tests/testthat/_snaps/plot/plot-means-showdata-4.svg b/tests/testthat/_snaps/plot/plot-means-showdata-4.svg deleted file mode 100644 index f98cc07be..000000000 --- a/tests/testthat/_snaps/plot/plot-means-showdata-4.svg +++ /dev/null @@ -1,291 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 -8 - - - - - - - - -setosa -versicolor -virginica -Species -Mean of Sepal.Length - -Sepal.Width - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -plot-means-showdata-4 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-1.svg b/tests/testthat/_snaps/plot/plot-relation-1.svg deleted file mode 100644 index 27d4a0275..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-1.svg +++ /dev/null @@ -1,60 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4.5 -5.0 -5.5 -6.0 -6.5 - - - - - - - - -setosa -versicolor -virginica -Species -Predicted value of Sepal.Length -plot-relation-1 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-2.svg b/tests/testthat/_snaps/plot/plot-relation-2.svg deleted file mode 100644 index 769d82b04..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-2.svg +++ /dev/null @@ -1,65 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - -3.5 -4.0 -4.5 -5.0 -5.5 -6.0 - - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Predicted value of Sepal.Length -plot-relation-2 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-3.svg b/tests/testthat/_snaps/plot/plot-relation-3.svg deleted file mode 100644 index 660315dfd..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-3.svg +++ /dev/null @@ -1,83 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Predicted value of Sepal.Length - -Species - - - - - - - - - -setosa -versicolor -virginica -plot-relation-3 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-4.svg b/tests/testthat/_snaps/plot/plot-relation-4.svg deleted file mode 100644 index 0fd7e46e5..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-4.svg +++ /dev/null @@ -1,115 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 - - - - - - - -setosa -versicolor -virginica -Species -Predicted value of Sepal.Length - -Sepal.Width - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -plot-relation-4 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-logistic-percentage-1.svg b/tests/testthat/_snaps/plot/plot-relation-logistic-percentage-1.svg deleted file mode 100644 index 89b3bcdd7..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-logistic-percentage-1.svg +++ /dev/null @@ -1,59 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - -20% -40% -60% -80% -100% - - - - - - - - - -3000 -4000 -5000 -6000 -body_mass -Predicted value of sex -plot-relation-logistic-percentage-1 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-multiple-ci-1.svg b/tests/testthat/_snaps/plot/plot-relation-multiple-ci-1.svg deleted file mode 100644 index 6e37260ee..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-multiple-ci-1.svg +++ /dev/null @@ -1,99 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -10 -15 -20 -25 -30 -35 - - - - - - - - - - -16 -18 -20 -22 -qsec -Predicted value of mpg -plot-relation-multiple-ci-1 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-showdata-1.svg b/tests/testthat/_snaps/plot/plot-relation-showdata-1.svg deleted file mode 100644 index c9247b699..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-showdata-1.svg +++ /dev/null @@ -1,208 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -5 -6 -7 -8 - - - - - - - -setosa -versicolor -virginica -Species -Predicted value of Sepal.Length -plot-relation-showdata-1 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-showdata-2.svg b/tests/testthat/_snaps/plot/plot-relation-showdata-2.svg deleted file mode 100644 index 33c324fad..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-showdata-2.svg +++ /dev/null @@ -1,213 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 -8 - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Predicted value of Sepal.Length -plot-relation-showdata-2 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-showdata-3.svg b/tests/testthat/_snaps/plot/plot-relation-showdata-3.svg deleted file mode 100644 index c0e6a2773..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-showdata-3.svg +++ /dev/null @@ -1,238 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 -8 - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Predicted value of Sepal.Length - -Species - - - - - - - - - - - - -setosa -versicolor -virginica -plot-relation-showdata-3 - - diff --git a/tests/testthat/_snaps/plot/plot-relation-showdata-4.svg b/tests/testthat/_snaps/plot/plot-relation-showdata-4.svg deleted file mode 100644 index f5aad50de..000000000 --- a/tests/testthat/_snaps/plot/plot-relation-showdata-4.svg +++ /dev/null @@ -1,267 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 -8 - - - - - - - - -setosa -versicolor -virginica -Species -Predicted value of Sepal.Length - -Sepal.Width - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -plot-relation-showdata-4 - - diff --git a/tests/testthat/_snaps/plot/plot-slopes-1.svg b/tests/testthat/_snaps/plot/plot-slopes-1.svg deleted file mode 100644 index 8873e711b..000000000 --- a/tests/testthat/_snaps/plot/plot-slopes-1.svg +++ /dev/null @@ -1,59 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -0.00 -0.25 -0.50 -0.75 - - - - - - - -setosa -versicolor -virginica -Species -Slope of Petal.Length -plot-slopes-1 - - diff --git a/tests/testthat/_snaps/plot/plot-slopes-2.svg b/tests/testthat/_snaps/plot/plot-slopes-2.svg deleted file mode 100644 index 235adf6fd..000000000 --- a/tests/testthat/_snaps/plot/plot-slopes-2.svg +++ /dev/null @@ -1,62 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - --0.4 --0.2 -0.0 -0.2 - - - - - - - - - - -0.0 -0.5 -1.0 -1.5 -2.0 -2.5 -Petal.Width -Slope of Petal.Length -plot-slopes-2 - - diff --git a/tests/testthat/_snaps/plot/plot-slopes-3.svg b/tests/testthat/_snaps/plot/plot-slopes-3.svg deleted file mode 100644 index c3cfa3a54..000000000 --- a/tests/testthat/_snaps/plot/plot-slopes-3.svg +++ /dev/null @@ -1,59 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -0.00 -0.25 -0.50 -0.75 - - - - - - - -setosa -versicolor -virginica -Species -Slope of Petal.Length -plot-slopes-3 - - diff --git a/tests/testthat/_snaps/plot/plot-slopes-4.svg b/tests/testthat/_snaps/plot/plot-slopes-4.svg deleted file mode 100644 index 38733308b..000000000 --- a/tests/testthat/_snaps/plot/plot-slopes-4.svg +++ /dev/null @@ -1,82 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - --0.4 --0.2 -0.0 -0.2 - - - - - - - - - - -0.0 -0.5 -1.0 -1.5 -2.0 -2.5 -Petal.Width -Slope of Petal.Length - -p - - - - - - -not significant -significant -plot-slopes-4 - - diff --git a/tests/testthat/_snaps/plot/plot-slopes-5.svg b/tests/testthat/_snaps/plot/plot-slopes-5.svg deleted file mode 100644 index 9ac487747..000000000 --- a/tests/testthat/_snaps/plot/plot-slopes-5.svg +++ /dev/null @@ -1,75 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -1 -2 -3 - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Slope of Species - -Comparison - - - - - - -versicolor - setosa -virginica - setosa -plot-slopes-5 - - diff --git a/tests/testthat/_snaps/print.md b/tests/testthat/_snaps/print.md deleted file mode 100644 index e6edff890..000000000 --- a/tests/testthat/_snaps/print.md +++ /dev/null @@ -1,365 +0,0 @@ -# estimate_means - using display() to print multiple by's - - Code - display(estimate_means(fit, c("c12hour = c(50, 100)", "c172code", "c161sex")), - format = "tt") - Output - - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | c12hour | c172code | c161sex | Mean | SE | 95% CI | t(791) | - +=========+=================================+=========+=======+======+================+========+ - | 50 | low level of education | Male | 11.05 | 0.84 | ( 9.40, 12.69) | 13.16 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 100 | low level of education | Male | 10.38 | 1.98 | ( 6.49, 14.26) | 5.25 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 50 | intermediate level of education | Male | 12.35 | 0.59 | (11.20, 13.50) | 21.05 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 100 | intermediate level of education | Male | 13.31 | 1.26 | (10.83, 15.78) | 10.54 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 50 | high level of education | Male | 11.70 | 0.67 | (10.39, 13.02) | 17.45 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 100 | high level of education | Male | 12.43 | 1.24 | (10.00, 14.87) | 10.01 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 50 | low level of education | Female | 11.99 | 0.33 | (11.35, 12.63) | 36.73 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 100 | low level of education | Female | 11.72 | 0.48 | (10.79, 12.66) | 24.61 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 50 | intermediate level of education | Female | 12.09 | 0.21 | (11.69, 12.50) | 58.05 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 100 | intermediate level of education | Female | 12.91 | 0.35 | (12.23, 13.60) | 37.19 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 50 | high level of education | Female | 12.84 | 0.42 | (12.01, 13.67) | 30.36 | - +---------+---------------------------------+---------+-------+------+----------------+--------+ - | 100 | high level of education | Female | 13.21 | 0.84 | (11.56, 14.85) | 15.75 | - +=========+=================================+=========+=======+======+================+========+ - | Variable predicted: neg_c_7
Predictors modulated: c12hour = c(50, 100), c172code, | - | c161sex
Predictors averaged: barthtot (65) | - +=========+=================================+=========+=======+======+================+========+ - Table: Estimated Marginal Means - -# estimate_contrasts - by with special character - - Code - print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects", - p_adjust = "holm"), table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p - -------------------------------------------------------------------------------- - mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999 - high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999 - high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999 - mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999 - high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.565 - high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.691 - mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999 - high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.368 - high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999 - - Variable predicted: neg_c_7 - Predictors contrasted: c172code - p-value adjustment method: Holm (1979) - ---- - - Code - print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects", - p_adjust = "holm"), table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(810) | p - ---------------------------------------------------------------------------------- - low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 - low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001 - mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999 - mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001 - mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001 - high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999 - high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.099 - high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001 - low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 - mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001 - mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999 - mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | 0.001 - high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001 - high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.636 - high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | > .999 - mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001 - mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001 - mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999 - high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001 - high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001 - high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.450 - mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 - mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001 - high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999 - high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.099 - high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001 - mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 - high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001 - high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.789 - high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.545 - high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001 - high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001 - high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999 - high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 - high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001 - high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 - - Variable predicted: neg_c_7 - Predictors contrasted: c172code, barthtot = [sd] - p-value adjustment method: Holm (1979) - ---- - - Code - print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p - ------------------------------------------------------------------------------- - mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596 - high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691 - high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360 - mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589 - high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071 - high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099 - mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221 - high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041 - high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181 - - Variable predicted: neg_c_7 - Predictors contrasted: c172code - p-values are uncorrected. - ---- - - Code - print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects"), - table_width = Inf, zap_small = TRUE) - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | SE | 95% CI | t(810) | p - ---------------------------------------------------------------------------------- - low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 - low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001 - mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596 - mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001 - mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001 - high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691 - high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.008 - high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001 - low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 - mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001 - mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589 - mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | < .001 - high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001 - high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071 - high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | 0.160 - mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001 - mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001 - mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221 - high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001 - high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001 - high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041 - mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 - mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001 - high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360 - high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.008 - high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001 - mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 - high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001 - high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099 - high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.055 - high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001 - high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001 - high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181 - high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 - high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001 - high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 - - Variable predicted: neg_c_7 - Predictors contrasted: c172code, barthtot = [sd] - p-values are uncorrected. - -# estimate_means - by is list - - Code - print(estimate_means(fit, list(c172code = c("low", "high"), c161sex = c( - "Female", "Male")), backend = "marginaleffects"), table_width = Inf, - zap_small = TRUE) - Output - Estimated Marginal Means - - c172code | c161sex | Mean | SE | 95% CI | t(825) - ----------------------------------------------------------- - low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44 - high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31 - low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25 - high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45 - - Variable predicted: neg_c_7 - Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male') - Predictors averaged: e16sex - ---- - - Code - print(estimate_means(fit, c("c172code = c('low', 'high')", - "c161sex = c('Female', 'Male')"), backend = "marginaleffects"), table_width = Inf, - zap_small = TRUE) - Output - Estimated Marginal Means - - c172code | c161sex | Mean | SE | 95% CI | t(825) - ----------------------------------------------------------- - low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44 - high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31 - low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25 - high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45 - - Variable predicted: neg_c_7 - Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male') - Predictors averaged: e16sex - -# estimate_epectation - don't print empty RE columns - - Code - print(estimate_expectation(m, by = "spp", predict = "conditional"), zap_small = TRUE) - Output - Model-based Predictions - - spp | Predicted | SE | CI - --------------------------------------- - GP | 0.73 | 0.21 | [0.32, 1.14] - PR | 0.42 | 0.16 | [0.11, 0.72] - DM | 0.94 | 0.25 | [0.45, 1.43] - EC-A | 0.60 | 0.19 | [0.24, 0.96] - EC-L | 1.42 | 0.37 | [0.69, 2.14] - DES-L | 1.34 | 0.36 | [0.63, 2.04] - DF | 0.78 | 0.21 | [0.37, 1.19] - - Variable predicted: count - Predictors modulated: spp - Predictors controlled: mined (yes) - Predictions are on the conditional-scale. - -# print - layouts and include data grid - - Code - print(out) - Output - Estimated Marginal Means - - Species | Mean | SE | 95% CI | t(147) - ------------------------------------------------ - setosa | 1.46 | 0.06 | [1.34, 1.58] | 24.02 - versicolor | 4.26 | 0.06 | [4.14, 4.38] | 70.00 - virginica | 5.55 | 0.06 | [5.43, 5.67] | 91.23 - - Variable predicted: Petal.Length - Predictors modulated: Species - ---- - - Code - print(out, select = "minimal") - Output - Estimated Marginal Means - - Species | Mean (CI) - ------------------------------ - setosa | 1.46 (1.34, 1.58) - versicolor | 4.26 (4.14, 4.38) - virginica | 5.55 (5.43, 5.67) - - Variable predicted: Petal.Length - Predictors modulated: Species - ---- - - Code - print(out, select = "minimal") - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference (CI) | p - ---------------------------------------------------- - versicolor | setosa | 2.80 (2.63, 2.97) | <0.001 - virginica | setosa | 4.09 (3.92, 4.26) | <0.001 - virginica | versicolor | 1.29 (1.12, 1.46) | <0.001 - - Variable predicted: Petal.Length - Predictors contrasted: Species - p-values are uncorrected. - ---- - - Code - print(out, select = "{estimate}{stars}|{ci}") - Output - Marginal Contrasts Analysis - - Level1 | Level2 | Difference | CI - ------------------------------------------------- - versicolor | setosa | 2.80*** | 2.63, 2.97 - virginica | setosa | 4.09*** | 3.92, 4.26 - virginica | versicolor | 1.29*** | 1.12, 1.46 - - Variable predicted: Petal.Length - Predictors contrasted: Species - p-values are uncorrected. - ---- - - Code - print(estimate_relation(m, by = "qsec")) - Output - Model-based Predictions - - qsec | Predicted | SE | 95% CI - --------------------------------------- - 14.50 | 2.80 | 0.19 | [2.41, 3.18] - 15.43 | 2.91 | 0.15 | [2.62, 3.21] - 16.37 | 3.03 | 0.11 | [2.81, 3.26] - 17.30 | 3.15 | 0.09 | [2.97, 3.32] - 18.23 | 3.27 | 0.08 | [3.10, 3.44] - 19.17 | 3.38 | 0.10 | [3.17, 3.60] - 20.10 | 3.50 | 0.14 | [3.21, 3.78] - 21.03 | 3.62 | 0.18 | [3.25, 3.98] - 21.97 | 3.73 | 0.22 | [3.28, 4.19] - 22.90 | 3.85 | 0.27 | [3.30, 4.40] - - Variable predicted: wt - Predictors modulated: qsec - Predictors controlled: mpg (20) - ---- - - Code - print(estimate_relation(m, by = "qsec"), include_grid = TRUE) - Output - Model-based Predictions - - qsec | mpg | Predicted | SE | 95% CI - ----------------------------------------------- - 14.50 | 20.09 | 2.80 | 0.19 | [2.41, 3.18] - 15.43 | 20.09 | 2.91 | 0.15 | [2.62, 3.21] - 16.37 | 20.09 | 3.03 | 0.11 | [2.81, 3.26] - 17.30 | 20.09 | 3.15 | 0.09 | [2.97, 3.32] - 18.23 | 20.09 | 3.27 | 0.08 | [3.10, 3.44] - 19.17 | 20.09 | 3.38 | 0.10 | [3.17, 3.60] - 20.10 | 20.09 | 3.50 | 0.14 | [3.21, 3.78] - 21.03 | 20.09 | 3.62 | 0.18 | [3.25, 3.98] - 21.97 | 20.09 | 3.73 | 0.22 | [3.28, 4.19] - 22.90 | 20.09 | 3.85 | 0.27 | [3.30, 4.40] - - Variable predicted: wt - Predictors modulated: qsec - Predictors controlled: mpg (20) - diff --git a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-1.svg b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-1.svg deleted file mode 100644 index 2b55f2cab..000000000 --- a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-1.svg +++ /dev/null @@ -1,384 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -0 -10 -20 -30 -40 -50 - - - - - - - - - -8 -10 -12 -x -Mean of y - -z - - - - - - - - - - - - --1.09 --0.06 -0.98 -plot-show_residuals-1 - - diff --git a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-2.svg b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-2.svg deleted file mode 100644 index b39dc5bd1..000000000 --- a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-2.svg +++ /dev/null @@ -1,407 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -0 -10 -20 -30 -40 -50 - - - - - - - - - -8 -10 -12 -x -Mean of y - -z - - - - - - - --2 -0 -2 -plot-show_residuals-2 - - diff --git a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-3.svg b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-3.svg deleted file mode 100644 index acc3e64be..000000000 --- a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-3.svg +++ /dev/null @@ -1,238 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -4 -5 -6 -7 -8 - - - - - - - - - - - -2.0 -2.5 -3.0 -3.5 -4.0 -4.5 -Sepal.Width -Mean of Sepal.Length - -Species - - - - - - - - - - - - -setosa -versicolor -virginica -plot-show_residuals-3 - - diff --git a/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.new.md b/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.new.md new file mode 100644 index 000000000..8d63eb2df --- /dev/null +++ b/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.new.md @@ -0,0 +1,21 @@ +# estimate_contrast, counterfactual, snapshots, Level-columns + + Code + print(out, table_width = Inf) + Output + Counterfactual Contrasts Analysis (G-computation) + + Level1 | Level2 | treatment | Difference | SE | 95% CI | z | p + --------------------------------------------------------------------------------- + post | pre | control | 1.85 | 1.22 | [-0.53, 4.23] | 1.52 | 0.128 + end | pre | control | 0.86 | 1.21 | [-1.51, 3.24] | 0.71 | 0.477 + end | post | control | -0.99 | 1.22 | [-3.37, 1.40] | -0.81 | 0.417 + post | pre | tx | 6.57 | 1.57 | [ 3.50, 9.65] | 4.19 | < .001 + end | pre | tx | 17.26 | 1.57 | [14.18, 20.34] | 10.99 | < .001 + end | post | tx | 10.69 | 1.57 | [ 7.62, 13.76] | 6.82 | < .001 + + Variable predicted: QoL + Predictors contrasted: time + Predictors averaged: education, hospital (0.95), age (0.22), phq4 (-0.076), ID + p-values are uncorrected. + From 42e9902f42b79ef79ca2d2b26f143d1d4fe48301 Mon Sep 17 00:00:00 2001 From: etiennebacher Date: Tue, 17 Feb 2026 18:40:19 +0100 Subject: [PATCH 2/5] accept --- .../estimate_contrasts_counterfactual.md | 2 +- .../estimate_contrasts_counterfactual.new.md | 21 ------------------- 2 files changed, 1 insertion(+), 22 deletions(-) delete mode 100644 tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.new.md diff --git a/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md b/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md index e8c7718b7..8d63eb2df 100644 --- a/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md +++ b/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md @@ -9,7 +9,7 @@ --------------------------------------------------------------------------------- post | pre | control | 1.85 | 1.22 | [-0.53, 4.23] | 1.52 | 0.128 end | pre | control | 0.86 | 1.21 | [-1.51, 3.24] | 0.71 | 0.477 - end | post | control | -0.99 | 1.22 | [-3.37, 1.39] | -0.81 | 0.417 + end | post | control | -0.99 | 1.22 | [-3.37, 1.40] | -0.81 | 0.417 post | pre | tx | 6.57 | 1.57 | [ 3.50, 9.65] | 4.19 | < .001 end | pre | tx | 17.26 | 1.57 | [14.18, 20.34] | 10.99 | < .001 end | post | tx | 10.69 | 1.57 | [ 7.62, 13.76] | 6.82 | < .001 diff --git a/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.new.md b/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.new.md deleted file mode 100644 index 8d63eb2df..000000000 --- a/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.new.md +++ /dev/null @@ -1,21 +0,0 @@ -# estimate_contrast, counterfactual, snapshots, Level-columns - - Code - print(out, table_width = Inf) - Output - Counterfactual Contrasts Analysis (G-computation) - - Level1 | Level2 | treatment | Difference | SE | 95% CI | z | p - --------------------------------------------------------------------------------- - post | pre | control | 1.85 | 1.22 | [-0.53, 4.23] | 1.52 | 0.128 - end | pre | control | 0.86 | 1.21 | [-1.51, 3.24] | 0.71 | 0.477 - end | post | control | -0.99 | 1.22 | [-3.37, 1.40] | -0.81 | 0.417 - post | pre | tx | 6.57 | 1.57 | [ 3.50, 9.65] | 4.19 | < .001 - end | pre | tx | 17.26 | 1.57 | [14.18, 20.34] | 10.99 | < .001 - end | post | tx | 10.69 | 1.57 | [ 7.62, 13.76] | 6.82 | < .001 - - Variable predicted: QoL - Predictors contrasted: time - Predictors averaged: education, hospital (0.95), age (0.22), phq4 (-0.076), ID - p-values are uncorrected. - From 578d3f51092efc82bdacd310cddb3a97b5261a09 Mon Sep 17 00:00:00 2001 From: etiennebacher Date: Tue, 17 Feb 2026 19:12:41 +0100 Subject: [PATCH 3/5] revert changes --- tests/testthat/_snaps/estimate_contrasts.md | 688 ++++++ 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tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-1.svg create mode 100644 tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-2.svg create mode 100644 tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-3.svg diff --git a/tests/testthat/_snaps/estimate_contrasts.md b/tests/testthat/_snaps/estimate_contrasts.md index 13b0fed2c..872e832a7 100644 --- a/tests/testthat/_snaps/estimate_contrasts.md +++ b/tests/testthat/_snaps/estimate_contrasts.md @@ -228,3 +228,691 @@ p-value adjustment method: Holm (1979) Contrasts are on the response-scale. +# estimate_contrasts - filtering works + + Code + print(estimate_contrasts(fit, "c172code", backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(827) | p + -------------------------------------------------------------------- + mid | low | -0.09 | 0.34 | [-0.76, 0.58] | -0.25 | 0.802 + high | low | 0.61 | 0.43 | [-0.24, 1.45] | 1.40 | 0.162 + high | mid | 0.69 | 0.36 | [-0.02, 1.40] | 1.92 | 0.055 + + Variable predicted: neg_c_7 + Predictors contrasted: c172code + Predictors averaged: e16sex, c161sex + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(fit, c("c161sex", "c172code"), backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(825) | p + ------------------------------------------------------------------------------- + Male, mid | Male, low | 0.29 | 0.71 | [-1.10, 1.68] | 0.41 | 0.684 + Male, high | Male, low | 0.69 | 0.83 | [-0.95, 2.32] | 0.82 | 0.410 + Female, low | Male, low | 1.05 | 0.69 | [-0.31, 2.40] | 1.51 | 0.131 + Female, mid | Male, low | 0.85 | 0.64 | [-0.40, 2.10] | 1.33 | 0.183 + Female, high | Male, low | 1.65 | 0.71 | [ 0.24, 3.05] | 2.30 | 0.022 + Male, high | Male, mid | 0.40 | 0.68 | [-0.94, 1.73] | 0.59 | 0.558 + Female, low | Male, mid | 0.76 | 0.50 | [-0.22, 1.73] | 1.52 | 0.129 + Female, mid | Male, mid | 0.56 | 0.42 | [-0.26, 1.38] | 1.35 | 0.178 + Female, high | Male, mid | 1.36 | 0.53 | [ 0.32, 2.39] | 2.58 | 0.010 + Female, low | Male, high | 0.36 | 0.66 | [-0.95, 1.66] | 0.54 | 0.589 + Female, mid | Male, high | 0.16 | 0.61 | [-1.03, 1.35] | 0.27 | 0.789 + Female, high | Male, high | 0.96 | 0.69 | [-0.39, 2.30] | 1.40 | 0.163 + Female, mid | Female, low | -0.20 | 0.39 | [-0.96, 0.57] | -0.51 | 0.613 + Female, high | Female, low | 0.60 | 0.51 | [-0.39, 1.59] | 1.18 | 0.236 + Female, high | Female, mid | 0.80 | 0.43 | [-0.04, 1.63] | 1.87 | 0.061 + + Variable predicted: neg_c_7 + Predictors contrasted: c161sex, c172code + Predictors averaged: e16sex + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(fit, "c161sex", "c172code", backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | c172code | Difference | SE | 95% CI | t(825) | p + ------------------------------------------------------------------------------- + Female | Male | low | 1.05 | 0.69 | [-0.31, 2.40] | 1.51 | 0.131 + Female | Male | mid | 0.56 | 0.42 | [-0.26, 1.38] | 1.35 | 0.178 + Female | Male | high | 0.96 | 0.69 | [-0.39, 2.30] | 1.40 | 0.163 + + Variable predicted: neg_c_7 + Predictors contrasted: c161sex + Predictors averaged: e16sex + p-values are uncorrected. + +--- + + Code + print(estimate_slopes(fit, "barthtot", backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Estimated Marginal Effects + + Slope | SE | 95% CI | t(810) | p + ----------------------------------------------- + -0.05 | 0.00 | [-0.06, -0.05] | -12.77 | < .001 + + Marginal effects estimated for barthtot + Type of slope was dY/dX + +--- + + Code + print(estimate_slopes(fit, "barthtot", by = "c172code", backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Estimated Marginal Effects + + c172code | Slope | SE | 95% CI | t(808) | p + ---------------------------------------------------------- + low | -0.06 | 0.01 | [-0.08, -0.05] | -7.08 | < .001 + mid | -0.05 | 0.01 | [-0.06, -0.04] | -9.82 | < .001 + high | -0.05 | 0.01 | [-0.07, -0.03] | -4.51 | < .001 + + Marginal effects estimated for barthtot + Type of slope was dY/dX + +--- + + Code + print(estimate_contrasts(fit, "barthtot", "c172code", backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(808) | p + -------------------------------------------------------------------- + mid | low | 0.01 | 0.01 | [-0.01, 0.03] | 1.17 | 0.243 + high | low | 0.02 | 0.01 | [-0.01, 0.04] | 1.10 | 0.271 + high | mid | 0.00 | 0.01 | [-0.02, 0.03] | 0.27 | 0.786 + + Variable predicted: neg_c_7 + Predictors contrasted: barthtot + Predictors averaged: e16sex, barthtot (65) + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(fit, "barthtot", c("c172code", "e16sex"), backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(803) | p + ------------------------------------------------------------------------------- + low, female | low, male | -0.01 | 0.02 | [-0.04, 0.03] | -0.35 | 0.729 + mid, male | low, male | -0.01 | 0.02 | [-0.04, 0.02] | -0.46 | 0.648 + mid, female | low, male | 0.02 | 0.01 | [-0.01, 0.05] | 1.24 | 0.217 + high, male | low, male | 0.00 | 0.02 | [-0.05, 0.04] | -0.16 | 0.876 + high, female | low, male | 0.02 | 0.02 | [-0.01, 0.06] | 1.19 | 0.236 + mid, male | low, female | 0.00 | 0.02 | [-0.03, 0.03] | -0.08 | 0.940 + mid, female | low, female | 0.02 | 0.01 | [ 0.00, 0.05] | 1.76 | 0.079 + high, male | low, female | 0.00 | 0.02 | [-0.04, 0.05] | 0.12 | 0.908 + high, female | low, female | 0.03 | 0.02 | [-0.01, 0.06] | 1.58 | 0.115 + mid, female | mid, male | 0.03 | 0.01 | [ 0.00, 0.05] | 2.24 | 0.026 + high, male | mid, male | 0.00 | 0.02 | [-0.04, 0.05] | 0.18 | 0.859 + high, female | mid, male | 0.03 | 0.02 | [ 0.00, 0.06] | 1.83 | 0.068 + high, male | mid, female | -0.02 | 0.02 | [-0.06, 0.02] | -1.08 | 0.280 + high, female | mid, female | 0.00 | 0.01 | [-0.02, 0.03] | 0.26 | 0.792 + high, female | high, male | 0.03 | 0.02 | [-0.02, 0.07] | 1.11 | 0.269 + + Variable predicted: neg_c_7 + Predictors contrasted: barthtot + Predictors averaged: barthtot (65) + p-values are uncorrected. + +# estimate_contrasts - simple contrasts and with - in levels works + + Code + print(estimate_contrasts(model, "Species", backend = "marginaleffects"), + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(146) | p + ---------------------------------------------------------------------------- + versicolor | setosa | 1.46 | 0.11 | [1.24, 1.68] | 13.01 | < .001 + virginica | setosa | 1.95 | 0.10 | [1.75, 2.14] | 19.47 | < .001 + virginica | versicolor | 0.49 | 0.09 | [0.31, 0.67] | 5.41 | < .001 + + Variable predicted: Sepal.Length + Predictors contrasted: Species + Predictors averaged: Sepal.Width (3.1) + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(m, c("time", "coffee"), backend = "marginaleffects"), + zap_small = TRUE, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(113) | p + --------------------------------------------------------------------------------------------- + morning, control | morning, coffee | -5.78 | 1.99 | [-9.73, -1.83] | -2.90 | 0.004 + noon, coffee | morning, coffee | -1.93 | 1.99 | [-5.88, 2.02] | -0.97 | 0.336 + noon, control | morning, coffee | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 + afternoon, coffee | morning, coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 + afternoon, control | morning, coffee | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 + noon, coffee | morning, control | 3.86 | 1.99 | [-0.09, 7.81] | 1.93 | 0.056 + noon, control | morning, control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 + afternoon, coffee | morning, control | 7.71 | 1.99 | [ 3.76, 11.66] | 3.87 | < .001 + afternoon, control | morning, control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 + noon, control | noon, coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 + afternoon, coffee | noon, coffee | 3.86 | 1.99 | [-0.09, 7.81] | 1.93 | 0.056 + afternoon, control | noon, coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 + afternoon, coffee | noon, control | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 + afternoon, control | noon, control | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 + afternoon, control | afternoon, coffee | -1.93 | 1.99 | [-5.88, 2.02] | -0.97 | 0.336 + + Variable predicted: alertness + Predictors contrasted: time, coffee + Predictors averaged: sex + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(m, contrast = "time", by = "coffee", backend = "marginaleffects"), + zap_small = TRUE, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | coffee | Difference | SE | 95% CI | t(113) | p + ----------------------------------------------------------------------------------- + noon | morning | coffee | -1.93 | 1.99 | [-5.88, 2.02] | -0.97 | 0.336 + afternoon | morning | coffee | 1.93 | 1.99 | [-2.02, 5.88] | 0.97 | 0.336 + afternoon | noon | coffee | 3.86 | 1.99 | [-0.09, 7.81] | 1.93 | 0.056 + noon | morning | control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 + afternoon | morning | control | 5.78 | 1.99 | [ 1.83, 9.73] | 2.90 | 0.004 + afternoon | noon | control | 0.00 | 1.99 | [-3.95, 3.95] | 0.00 | > .999 + + Variable predicted: alertness + Predictors contrasted: time + Predictors averaged: sex + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model, contrast = c("mined", "spp"), backend = "marginaleffects"), + zap_small = TRUE, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | z | p + ----------------------------------------------------------------------------- + yes, PR | yes, GP | 0.06 | 0.05 | [-0.04, 0.16] | 1.10 | 0.271 + yes, DM | yes, GP | 0.32 | 0.11 | [ 0.10, 0.54] | 2.89 | 0.004 + yes, EC-A | yes, GP | 0.04 | 0.05 | [-0.05, 0.13] | 0.80 | 0.421 + yes, EC-L | yes, GP | 0.17 | 0.08 | [ 0.02, 0.32] | 2.19 | 0.028 + yes, DES-L | yes, GP | 0.43 | 0.14 | [ 0.17, 0.70] | 3.19 | 0.001 + yes, DF | yes, GP | 0.43 | 0.14 | [ 0.17, 0.70] | 3.19 | 0.001 + no, GP | yes, GP | 2.59 | 0.55 | [ 1.50, 3.67] | 4.67 | < .001 + no, PR | yes, GP | 0.51 | 0.16 | [ 0.20, 0.82] | 3.21 | 0.001 + no, DM | yes, GP | 2.86 | 0.61 | [ 1.68, 4.05] | 4.73 | < .001 + no, EC-A | yes, GP | 1.10 | 0.27 | [ 0.57, 1.64] | 4.03 | < .001 + no, EC-L | yes, GP | 4.67 | 0.94 | [ 2.82, 6.52] | 4.95 | < .001 + no, DES-L | yes, GP | 4.62 | 0.93 | [ 2.79, 6.45] | 4.95 | < .001 + no, DF | yes, GP | 2.24 | 0.49 | [ 1.28, 3.20] | 4.58 | < .001 + yes, DM | yes, PR | 0.26 | 0.11 | [ 0.05, 0.48] | 2.43 | 0.015 + yes, EC-A | yes, PR | -0.02 | 0.06 | [-0.13, 0.09] | -0.33 | 0.740 + yes, EC-L | yes, PR | 0.11 | 0.08 | [-0.04, 0.27] | 1.43 | 0.154 + yes, DES-L | yes, PR | 0.38 | 0.13 | [ 0.12, 0.64] | 2.86 | 0.004 + yes, DF | yes, PR | 0.38 | 0.13 | [ 0.12, 0.64] | 2.86 | 0.004 + no, GP | yes, PR | 2.53 | 0.56 | [ 1.44, 3.62] | 4.54 | < .001 + no, PR | yes, PR | 0.45 | 0.16 | [ 0.13, 0.77] | 2.75 | 0.006 + no, DM | yes, PR | 2.80 | 0.61 | [ 1.61, 4.00] | 4.61 | < .001 + no, EC-A | yes, PR | 1.05 | 0.28 | [ 0.50, 1.59] | 3.76 | < .001 + no, EC-L | yes, PR | 4.61 | 0.95 | [ 2.76, 6.47] | 4.87 | < .001 + no, DES-L | yes, PR | 4.56 | 0.94 | [ 2.73, 6.40] | 4.87 | < .001 + no, DF | yes, PR | 2.18 | 0.49 | [ 1.22, 3.15] | 4.44 | < .001 + yes, EC-A | yes, DM | -0.28 | 0.11 | [-0.50, -0.07] | -2.59 | 0.010 + yes, EC-L | yes, DM | -0.15 | 0.11 | [-0.36, 0.06] | -1.39 | 0.164 + yes, DES-L | yes, DM | 0.11 | 0.13 | [-0.14, 0.36] | 0.89 | 0.375 + yes, DF | yes, DM | 0.11 | 0.13 | [-0.14, 0.36] | 0.89 | 0.375 + no, GP | yes, DM | 2.27 | 0.58 | [ 1.14, 3.40] | 3.93 | < .001 + no, PR | yes, DM | 0.19 | 0.20 | [-0.21, 0.58] | 0.93 | 0.352 + no, DM | yes, DM | 2.54 | 0.63 | [ 1.31, 3.77] | 4.04 | < .001 + no, EC-A | yes, DM | 0.78 | 0.31 | [ 0.18, 1.38] | 2.56 | 0.011 + no, EC-L | yes, DM | 4.35 | 0.96 | [ 2.46, 6.24] | 4.51 | < .001 + no, DES-L | yes, DM | 4.30 | 0.95 | [ 2.43, 6.17] | 4.51 | < .001 + no, DF | yes, DM | 1.92 | 0.51 | [ 0.91, 2.93] | 3.74 | < .001 + yes, EC-L | yes, EC-A | 0.13 | 0.08 | [-0.02, 0.29] | 1.68 | 0.093 + yes, DES-L | yes, EC-A | 0.40 | 0.13 | [ 0.14, 0.66] | 2.97 | 0.003 + yes, DF | yes, EC-A | 0.40 | 0.13 | [ 0.14, 0.66] | 2.97 | 0.003 + no, GP | yes, EC-A | 2.55 | 0.56 | [ 1.46, 3.64] | 4.58 | < .001 + no, PR | yes, EC-A | 0.47 | 0.16 | [ 0.15, 0.79] | 2.90 | 0.004 + no, DM | yes, EC-A | 2.82 | 0.61 | [ 1.63, 4.01] | 4.65 | < .001 + no, EC-A | yes, EC-A | 1.06 | 0.28 | [ 0.52, 1.61] | 3.85 | < .001 + no, EC-L | yes, EC-A | 4.63 | 0.95 | [ 2.78, 6.48] | 4.90 | < .001 + no, DES-L | yes, EC-A | 4.58 | 0.94 | [ 2.75, 6.42] | 4.90 | < .001 + no, DF | yes, EC-A | 2.20 | 0.49 | [ 1.24, 3.17] | 4.49 | < .001 + yes, DES-L | yes, EC-L | 0.26 | 0.13 | [ 0.02, 0.51] | 2.08 | 0.037 + yes, DF | yes, EC-L | 0.26 | 0.13 | [ 0.02, 0.51] | 2.08 | 0.037 + no, GP | yes, EC-L | 2.42 | 0.57 | [ 1.31, 3.53] | 4.28 | < .001 + no, PR | yes, EC-L | 0.34 | 0.18 | [-0.01, 0.69] | 1.89 | 0.058 + no, DM | yes, EC-L | 2.69 | 0.62 | [ 1.48, 3.90] | 4.37 | < .001 + no, EC-A | yes, EC-L | 0.93 | 0.29 | [ 0.37, 1.50] | 3.23 | 0.001 + no, EC-L | yes, EC-L | 4.50 | 0.95 | [ 2.63, 6.37] | 4.72 | < .001 + no, DES-L | yes, EC-L | 4.45 | 0.94 | [ 2.60, 6.30] | 4.71 | < .001 + no, DF | yes, EC-L | 2.07 | 0.50 | [ 1.09, 3.05] | 4.14 | < .001 + yes, DF | yes, DES-L | 0.00 | 0.13 | [-0.26, 0.26] | 0.00 | > .999 + no, GP | yes, DES-L | 2.15 | 0.59 | [ 1.00, 3.31] | 3.67 | < .001 + no, PR | yes, DES-L | 0.07 | 0.22 | [-0.36, 0.50] | 0.33 | 0.738 + no, DM | yes, DES-L | 2.43 | 0.64 | [ 1.18, 3.68] | 3.81 | < .001 + no, EC-A | yes, DES-L | 0.67 | 0.32 | [ 0.04, 1.29] | 2.09 | 0.037 + no, EC-L | yes, DES-L | 4.24 | 0.97 | [ 2.33, 6.14] | 4.36 | < .001 + no, DES-L | yes, DES-L | 4.19 | 0.96 | [ 2.30, 6.07] | 4.35 | < .001 + no, DF | yes, DES-L | 1.81 | 0.52 | [ 0.78, 2.83] | 3.45 | < .001 + no, GP | yes, DF | 2.15 | 0.59 | [ 1.00, 3.31] | 3.67 | < .001 + no, PR | yes, DF | 0.07 | 0.22 | [-0.36, 0.50] | 0.33 | 0.738 + no, DM | yes, DF | 2.43 | 0.64 | [ 1.18, 3.68] | 3.81 | < .001 + no, EC-A | yes, DF | 0.67 | 0.32 | [ 0.04, 1.29] | 2.09 | 0.037 + no, EC-L | yes, DF | 4.24 | 0.97 | [ 2.33, 6.14] | 4.36 | < .001 + no, DES-L | yes, DF | 4.19 | 0.96 | [ 2.30, 6.07] | 4.35 | < .001 + no, DF | yes, DF | 1.81 | 0.52 | [ 0.78, 2.83] | 3.45 | < .001 + no, PR | no, GP | -2.08 | 0.48 | [-3.02, -1.14] | -4.35 | < .001 + no, DM | no, GP | 0.27 | 0.37 | [-0.46, 1.00] | 0.73 | 0.466 + no, EC-A | no, GP | -1.49 | 0.41 | [-2.29, -0.68] | -3.61 | < .001 + no, EC-L | no, GP | 2.08 | 0.58 | [ 0.95, 3.21] | 3.61 | < .001 + no, DES-L | no, GP | 2.03 | 0.57 | [ 0.92, 3.15] | 3.57 | < .001 + no, DF | no, GP | -0.35 | 0.35 | [-1.04, 0.35] | -0.98 | 0.328 + no, DM | no, PR | 2.35 | 0.53 | [ 1.32, 3.39] | 4.47 | < .001 + no, EC-A | no, PR | 0.59 | 0.23 | [ 0.14, 1.05] | 2.56 | 0.011 + no, EC-L | no, PR | 4.16 | 0.86 | [ 2.49, 5.84] | 4.87 | < .001 + no, DES-L | no, PR | 4.11 | 0.85 | [ 2.45, 5.77] | 4.86 | < .001 + no, DF | no, PR | 1.73 | 0.42 | [ 0.92, 2.55] | 4.15 | < .001 + no, EC-A | no, DM | -1.76 | 0.46 | [-2.65, -0.87] | -3.86 | < .001 + no, EC-L | no, DM | 1.81 | 0.55 | [ 0.73, 2.89] | 3.29 | < .001 + no, DES-L | no, DM | 1.76 | 0.54 | [ 0.70, 2.82] | 3.24 | 0.001 + no, DF | no, DM | -0.62 | 0.38 | [-1.36, 0.12] | -1.65 | 0.100 + no, EC-L | no, EC-A | 3.57 | 0.77 | [ 2.07, 5.07] | 4.66 | < .001 + no, DES-L | no, EC-A | 3.52 | 0.76 | [ 2.03, 5.00] | 4.65 | < .001 + no, DF | no, EC-A | 1.14 | 0.36 | [ 0.43, 1.85] | 3.16 | 0.002 + no, DES-L | no, EC-L | -0.05 | 0.48 | [-0.99, 0.89] | -0.10 | 0.918 + no, DF | no, EC-L | -2.43 | 0.61 | [-3.63, -1.22] | -3.95 | < .001 + no, DF | no, DES-L | -2.38 | 0.61 | [-3.57, -1.19] | -3.92 | < .001 + + Variable predicted: count + Predictors contrasted: mined, spp + Predictors averaged: cover (8.7e-11), site + p-values are uncorrected. + Contrasts are on the response-scale. + +--- + + Code + print(estimate_contrasts(model, contrast = "mined", by = "spp", backend = "marginaleffects"), + zap_small = TRUE, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | spp | Difference | SE | 95% CI | z | p + -------------------------------------------------------------------------- + no | yes | GP | 2.59 | 0.55 | [1.50, 3.67] | 4.67 | < .001 + no | yes | PR | 0.45 | 0.16 | [0.13, 0.77] | 2.75 | 0.006 + no | yes | DM | 2.54 | 0.63 | [1.31, 3.77] | 4.04 | < .001 + no | yes | EC-A | 1.06 | 0.28 | [0.52, 1.61] | 3.85 | < .001 + no | yes | EC-L | 4.50 | 0.95 | [2.63, 6.37] | 4.72 | < .001 + no | yes | DES-L | 4.19 | 0.96 | [2.30, 6.07] | 4.35 | < .001 + no | yes | DF | 1.81 | 0.52 | [0.78, 2.83] | 3.45 | < .001 + + Variable predicted: count + Predictors contrasted: mined + Predictors averaged: cover (8.7e-11), site + p-values are uncorrected. + Contrasts are on the response-scale. + +# estimate_contrasts - examples from docs work as intendec + + Code + print(estimate_contrasts(model, contrast = "Petal.Width", by = "Species"), + zap_small = TRUE, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(144) | p + ---------------------------------------------------------------------------- + versicolor | setosa | 0.22 | 0.46 | [-0.70, 1.13] | 0.47 | 0.640 + virginica | setosa | -0.21 | 0.44 | [-1.07, 0.66] | -0.47 | 0.638 + virginica | versicolor | -0.42 | 0.27 | [-0.95, 0.11] | -1.58 | 0.116 + + Variable predicted: Sepal.Width + Predictors contrasted: Petal.Width + Predictors averaged: Petal.Width (1.2) + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model, contrast = c("Species", "Petal.Width"), length = 2), + zap_small = TRUE, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(144) | p + ---------------------------------------------------------------------------------------- + setosa, 2.5 | setosa, 0.1 | 2.01 | 0.98 | [ 0.08, 3.94] | 2.06 | 0.041 + versicolor, 0.1 | setosa, 0.1 | -1.83 | 0.28 | [-2.38, -1.28] | -6.55 | < .001 + versicolor, 2.5 | setosa, 0.1 | 0.70 | 0.27 | [ 0.17, 1.23] | 2.61 | 0.010 + virginica, 0.1 | setosa, 0.1 | -1.55 | 0.31 | [-2.17, -0.93] | -4.95 | < .001 + virginica, 2.5 | setosa, 0.1 | -0.03 | 0.11 | [-0.25, 0.19] | -0.29 | 0.773 + versicolor, 0.1 | setosa, 2.5 | -3.84 | 0.96 | [-5.73, -1.95] | -4.01 | < .001 + versicolor, 2.5 | setosa, 2.5 | -1.31 | 0.95 | [-3.19, 0.58] | -1.37 | 0.172 + virginica, 0.1 | setosa, 2.5 | -3.56 | 0.97 | [-5.47, -1.65] | -3.68 | < .001 + virginica, 2.5 | setosa, 2.5 | -2.04 | 0.92 | [-3.86, -0.22] | -2.21 | 0.028 + versicolor, 2.5 | versicolor, 0.1 | 2.53 | 0.52 | [ 1.50, 3.56] | 4.86 | < .001 + virginica, 0.1 | versicolor, 0.1 | 0.28 | 0.41 | [-0.52, 1.08] | 0.69 | 0.492 + virginica, 2.5 | versicolor, 0.1 | 1.80 | 0.28 | [ 1.24, 2.35] | 6.35 | < .001 + virginica, 0.1 | versicolor, 2.5 | -2.25 | 0.40 | [-3.04, -1.46] | -5.64 | < .001 + virginica, 2.5 | versicolor, 2.5 | -0.73 | 0.27 | [-1.27, -0.20] | -2.70 | 0.008 + virginica, 2.5 | virginica, 0.1 | 1.52 | 0.37 | [ 0.77, 2.26] | 4.04 | < .001 + + Variable predicted: Sepal.Width + Predictors contrasted: Species, Petal.Width + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model, contrast = c("Species", "Petal.Width=c(1, 2)")), + zap_small = TRUE, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(144) | p + ------------------------------------------------------------------------------------ + setosa, 2 | setosa, 1 | 0.84 | 0.41 | [ 0.03, 1.64] | 2.06 | 0.041 + versicolor, 1 | setosa, 1 | -1.63 | 0.32 | [-2.27, -1.00] | -5.09 | < .001 + versicolor, 2 | setosa, 1 | -0.58 | 0.35 | [-1.26, 0.10] | -1.68 | 0.096 + virginica, 1 | setosa, 1 | -1.73 | 0.35 | [-2.43, -1.04] | -4.93 | < .001 + virginica, 2 | setosa, 1 | -1.10 | 0.31 | [-1.72, -0.48] | -3.52 | < .001 + versicolor, 1 | setosa, 2 | -2.47 | 0.72 | [-3.89, -1.05] | -3.43 | < .001 + versicolor, 2 | setosa, 2 | -1.42 | 0.73 | [-2.86, 0.03] | -1.94 | 0.055 + virginica, 1 | setosa, 2 | -2.57 | 0.73 | [-4.02, -1.12] | -3.50 | < .001 + virginica, 2 | setosa, 2 | -1.94 | 0.72 | [-3.35, -0.52] | -2.71 | 0.008 + versicolor, 2 | versicolor, 1 | 1.05 | 0.22 | [ 0.62, 1.48] | 4.86 | < .001 + virginica, 1 | versicolor, 1 | -0.10 | 0.19 | [-0.47, 0.27] | -0.54 | 0.589 + virginica, 2 | versicolor, 1 | 0.53 | 0.09 | [ 0.35, 0.71] | 5.72 | < .001 + virginica, 1 | versicolor, 2 | -1.15 | 0.23 | [-1.60, -0.71] | -5.13 | < .001 + virginica, 2 | versicolor, 2 | -0.52 | 0.16 | [-0.84, -0.21] | -3.31 | 0.001 + virginica, 2 | virginica, 1 | 0.63 | 0.16 | [ 0.32, 0.94] | 4.04 | < .001 + + Variable predicted: Sepal.Width + Predictors contrasted: Species, Petal.Width=c(1, 2) + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model, by = "Petal.Width", length = 4), zap_small = TRUE, + table_width = Inf) + Message + We selected `contrast=c("Species")`. + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Petal.Width | Difference | SE | 95% CI | t(144) | p + -------------------------------------------------------------------------------------------- + versicolor | setosa | 0.10 | -1.83 | 0.28 | [-2.38, -1.28] | -6.55 | < .001 + virginica | setosa | 0.10 | -1.55 | 0.31 | [-2.17, -0.93] | -4.95 | < .001 + virginica | versicolor | 0.10 | 0.28 | 0.41 | [-0.52, 1.08] | 0.69 | 0.492 + versicolor | setosa | 0.90 | -1.65 | 0.29 | [-2.22, -1.08] | -5.74 | < .001 + virginica | setosa | 0.90 | -1.71 | 0.32 | [-2.35, -1.07] | -5.28 | < .001 + virginica | versicolor | 0.90 | -0.06 | 0.21 | [-0.47, 0.35] | -0.28 | 0.780 + versicolor | setosa | 1.70 | -1.48 | 0.60 | [-2.67, -0.29] | -2.47 | 0.015 + virginica | setosa | 1.70 | -1.88 | 0.60 | [-3.06, -0.70] | -3.14 | 0.002 + virginica | versicolor | 1.70 | -0.40 | 0.11 | [-0.62, -0.17] | -3.50 | < .001 + versicolor | setosa | 2.50 | -1.31 | 0.95 | [-3.19, 0.58] | -1.37 | 0.172 + virginica | setosa | 2.50 | -2.04 | 0.92 | [-3.86, -0.22] | -2.21 | 0.028 + virginica | versicolor | 2.50 | -0.73 | 0.27 | [-1.27, -0.20] | -2.70 | 0.008 + + Variable predicted: Sepal.Width + Predictors contrasted: Species + p-values are uncorrected. + +# estimate_contrasts - test all combinations of contrast and by, with filtering + + Code + print(estimate_contrasts(model2, c("grp", "time", "x")), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(992) | p + -------------------------------------------------------------------------------------- + control, 1, b | control, 1, a | 0.15 | 0.13 | [-0.10, 0.40] | 1.20 | 0.231 + control, 2, a | control, 1, a | 0.03 | 0.13 | [-0.23, 0.28] | 0.19 | 0.847 + control, 2, b | control, 1, a | 0.09 | 0.13 | [-0.16, 0.34] | 0.73 | 0.465 + treatment, 1, a | control, 1, a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 + treatment, 1, b | control, 1, a | -0.03 | 0.13 | [-0.28, 0.22] | -0.22 | 0.824 + treatment, 2, a | control, 1, a | 0.02 | 0.13 | [-0.23, 0.27] | 0.19 | 0.850 + treatment, 2, b | control, 1, a | 0.05 | 0.12 | [-0.19, 0.28] | 0.37 | 0.712 + control, 2, a | control, 1, b | -0.12 | 0.13 | [-0.38, 0.13] | -0.97 | 0.332 + control, 2, b | control, 1, b | -0.06 | 0.12 | [-0.30, 0.19] | -0.46 | 0.648 + treatment, 1, a | control, 1, b | 0.04 | 0.13 | [-0.20, 0.29] | 0.34 | 0.730 + treatment, 1, b | control, 1, b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 + treatment, 2, a | control, 1, b | -0.13 | 0.12 | [-0.37, 0.12] | -1.02 | 0.307 + treatment, 2, b | control, 1, b | -0.10 | 0.12 | [-0.34, 0.13] | -0.89 | 0.376 + control, 2, b | control, 2, a | 0.07 | 0.13 | [-0.19, 0.32] | 0.52 | 0.604 + treatment, 1, a | control, 2, a | 0.17 | 0.13 | [-0.09, 0.43] | 1.26 | 0.207 + treatment, 1, b | control, 2, a | -0.05 | 0.13 | [-0.31, 0.20] | -0.41 | 0.680 + treatment, 2, a | control, 2, a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 + treatment, 2, b | control, 2, a | 0.02 | 0.13 | [-0.23, 0.27] | 0.16 | 0.876 + treatment, 1, a | control, 2, b | 0.10 | 0.13 | [-0.15, 0.35] | 0.78 | 0.437 + treatment, 1, b | control, 2, b | -0.12 | 0.13 | [-0.37, 0.12] | -0.97 | 0.333 + treatment, 2, a | control, 2, b | -0.07 | 0.13 | [-0.32, 0.18] | -0.55 | 0.582 + treatment, 2, b | control, 2, b | -0.05 | 0.12 | [-0.29, 0.19] | -0.40 | 0.691 + treatment, 1, b | treatment, 1, a | -0.22 | 0.13 | [-0.47, 0.03] | -1.73 | 0.083 + treatment, 2, a | treatment, 1, a | -0.17 | 0.13 | [-0.42, 0.08] | -1.32 | 0.187 + treatment, 2, b | treatment, 1, a | -0.15 | 0.12 | [-0.39, 0.09] | -1.20 | 0.230 + treatment, 2, a | treatment, 1, b | 0.05 | 0.12 | [-0.19, 0.30] | 0.42 | 0.676 + treatment, 2, b | treatment, 1, b | 0.07 | 0.12 | [-0.16, 0.31] | 0.61 | 0.541 + treatment, 2, b | treatment, 2, a | 0.02 | 0.12 | [-0.21, 0.26] | 0.18 | 0.861 + + Variable predicted: score + Predictors contrasted: grp, time, x + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, c("grp", "time"), by = "x"), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | x | Difference | SE | 95% CI | t(992) | p + ------------------------------------------------------------------------------------ + control, 2 | control, 1 | a | 0.03 | 0.13 | [-0.23, 0.28] | 0.19 | 0.847 + treatment, 1 | control, 1 | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 + treatment, 2 | control, 1 | a | 0.02 | 0.13 | [-0.23, 0.27] | 0.19 | 0.850 + treatment, 1 | control, 2 | a | 0.17 | 0.13 | [-0.09, 0.43] | 1.26 | 0.207 + treatment, 2 | control, 2 | a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 + treatment, 2 | treatment, 1 | a | -0.17 | 0.13 | [-0.42, 0.08] | -1.32 | 0.187 + control, 2 | control, 1 | b | -0.06 | 0.12 | [-0.30, 0.19] | -0.46 | 0.648 + treatment, 1 | control, 1 | b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 + treatment, 2 | control, 1 | b | -0.10 | 0.12 | [-0.34, 0.13] | -0.89 | 0.376 + treatment, 1 | control, 2 | b | -0.12 | 0.13 | [-0.37, 0.12] | -0.97 | 0.333 + treatment, 2 | control, 2 | b | -0.05 | 0.12 | [-0.29, 0.19] | -0.40 | 0.691 + treatment, 2 | treatment, 1 | b | 0.07 | 0.12 | [-0.16, 0.31] | 0.61 | 0.541 + + Variable predicted: score + Predictors contrasted: grp, time + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, "grp", by = c("time", "x")), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | time | x | Difference | SE | 95% CI | t(992) | p + ----------------------------------------------------------------------------------- + treatment | control | 1 | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 + treatment | control | 2 | a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 + treatment | control | 1 | b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 + treatment | control | 2 | b | -0.05 | 0.12 | [-0.29, 0.19] | -0.40 | 0.691 + + Variable predicted: score + Predictors contrasted: grp + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, "grp", by = "time"), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | time | Difference | SE | 95% CI | t(992) | p + ------------------------------------------------------------------------------- + treatment | control | 1 | 0.01 | 0.09 | [-0.17, 0.18] | 0.09 | 0.931 + treatment | control | 2 | -0.02 | 0.09 | [-0.20, 0.15] | -0.28 | 0.780 + + Variable predicted: score + Predictors contrasted: grp + Predictors averaged: x + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, c("grp", "time", "x='a'")), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(992) | p + -------------------------------------------------------------------------------- + control, 2 | control, 1 | 0.03 | 0.13 | [-0.23, 0.28] | 0.19 | 0.847 + treatment, 1 | control, 1 | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 + treatment, 2 | control, 1 | 0.02 | 0.13 | [-0.23, 0.27] | 0.19 | 0.850 + treatment, 1 | control, 2 | 0.17 | 0.13 | [-0.09, 0.43] | 1.26 | 0.207 + treatment, 2 | control, 2 | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 + treatment, 2 | treatment, 1 | -0.17 | 0.13 | [-0.42, 0.08] | -1.32 | 0.187 + + Variable predicted: score + Predictors contrasted: grp, time, x='a' + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, c("grp", "time=1"), by = "x"), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | x | Difference | SE | 95% CI | t(992) | p + ---------------------------------------------------------------------------- + treatment | control | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 + treatment | control | b | -0.18 | 0.12 | [-0.42, 0.06] | -1.45 | 0.147 + + Variable predicted: score + Predictors contrasted: grp, time=1 + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, "grp", by = c("time", "x='a'")), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | time | x | Difference | SE | 95% CI | t(992) | p + ----------------------------------------------------------------------------------- + treatment | control | 1 | a | 0.19 | 0.13 | [-0.06, 0.45] | 1.49 | 0.137 + treatment | control | 2 | a | 0.00 | 0.13 | [-0.26, 0.25] | -0.01 | 0.991 + + Variable predicted: score + Predictors contrasted: grp + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, "time=c(1,2)", by = "grp"), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | grp | Difference | SE | 95% CI | t(994) | p + -------------------------------------------------------------------------------- + 2 | 1 | control | 0.14 | 0.11 | [-0.08, 0.36] | 1.24 | 0.216 + 2 | 1 | treatment | -0.07 | 0.11 | [-0.28, 0.14] | -0.63 | 0.529 + + Variable predicted: score + Predictors contrasted: time=c(1,2) + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(model2, c("grp", "time=2")), zap_small = TRUE, + table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(994) | p + ------------------------------------------------------------------------ + treatment | control | -0.15 | 0.11 | [-0.36, 0.05] | -1.47 | 0.143 + + Variable predicted: score + Predictors contrasted: grp, time=2 + p-values are uncorrected. + +# estimate_contrast, slopes with emmeans + + Code + print(out, table_width = Inf) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | 95% CI | p + ---------------------------------------------------------- + 0, 0.725 | 0, -2.012 | 1.12 | [0.37, 3.43] | 0.839 + 0, 3.463 | 0, -2.012 | 1.26 | [0.14, 11.76] | 0.839 + 1, -2.012 | 0, -2.012 | 1.00 | [0.35, 2.82] | 0.999 + 1, 0.725 | 0, -2.012 | 1.12 | [0.23, 5.43] | 0.887 + 1, 3.463 | 0, -2.012 | 1.26 | [0.10, 15.76] | 0.858 + 0, 3.463 | 0, 0.725 | 1.12 | [0.37, 3.43] | 0.839 + 1, -2.012 | 0, 0.725 | 0.89 | [0.20, 3.87] | 0.877 + 1, 0.725 | 0, 0.725 | 1.00 | [0.35, 2.82] | 0.999 + 1, 3.463 | 0, 0.725 | 1.12 | [0.23, 5.43] | 0.887 + 1, -2.012 | 0, 3.463 | 0.79 | [0.07, 8.71] | 0.849 + 1, 0.725 | 0, 3.463 | 0.89 | [0.20, 3.87] | 0.877 + 1, 3.463 | 0, 3.463 | 1.00 | [0.35, 2.82] | 0.999 + 1, 0.725 | 1, -2.012 | 1.12 | [0.37, 3.43] | 0.839 + 1, 3.463 | 1, -2.012 | 1.26 | [0.14, 11.76] | 0.839 + 1, 3.463 | 1, 0.725 | 1.12 | [0.37, 3.43] | 0.839 + + Variable predicted: outcome + Predictors contrasted: var_binom, var_cont + p-values are uncorrected. + Contrasts are on the link-scale. + diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-1.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-1.svg new file mode 100644 index 000000000..a240b7a4b --- /dev/null +++ b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-1.svg @@ -0,0 +1,130 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Male + + + + + + + + + + +Female + + + + + + +0 +50 +100 +150 + + + + +0 +50 +100 +150 +5 +10 +15 + + + +average number of hours of care per week +Mean of Negative impact with 7 items + +carer's level of education + + + + + + + + + +low level of education +intermediate level of education +high level of education +plot-interaction-facets-1 + + diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-10.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-10.svg new file mode 100644 index 000000000..1dad556c1 --- /dev/null +++ b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-10.svg @@ -0,0 +1,257 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Male + + + + + + + + + + +Female + + + + + + + + + + +low level of education + + + + + + + + + + +intermediate level of education + + + + + + + + + + +high level of education + + + + + + +0 +50 +100 +150 + + + + +0 +50 +100 +150 +-10 +0 +10 +20 +30 +40 + + + + + + +-10 +0 +10 +20 +30 +40 + + + + + + +-10 +0 +10 +20 +30 +40 + + + + + + +average number of hours of care per week +Mean of Negative impact with 7 items + +elder's gender + + + + + + +male +female +plot-interaction-facets-10 + + diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-2.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-2.svg new file mode 100644 index 000000000..f161d681f --- /dev/null +++ b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-2.svg @@ -0,0 +1,113 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +10 +12 +14 +16 +18 + + + + + + + + + +0 +50 +100 +150 +average number of hours of care per week +Mean of Negative impact with 7 items + +barthtot + + + + + + + + + + +0 +25 +50 +75 +100 + +carer's level of education + + + + + + +low level of education +intermediate level of education +high level of education +plot-interaction-facets-2 + + diff --git a/tests/testthat/_snaps/plot-facet/plot-interaction-facets-3.svg b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-3.svg new file mode 100644 index 000000000..f44989580 --- /dev/null +++ b/tests/testthat/_snaps/plot-facet/plot-interaction-facets-3.svg @@ -0,0 +1,708 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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b/tests/testthat/_snaps/print.md @@ -0,0 +1,365 @@ +# estimate_means - using display() to print multiple by's + + Code + display(estimate_means(fit, c("c12hour = c(50, 100)", "c172code", "c161sex")), + format = "tt") + Output + + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | c12hour | c172code | c161sex | Mean | SE | 95% CI | t(791) | + +=========+=================================+=========+=======+======+================+========+ + | 50 | low level of education | Male | 11.05 | 0.84 | ( 9.40, 12.69) | 13.16 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 100 | low level of education | Male | 10.38 | 1.98 | ( 6.49, 14.26) | 5.25 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 50 | intermediate level of education | Male | 12.35 | 0.59 | (11.20, 13.50) | 21.05 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 100 | intermediate level of education | Male | 13.31 | 1.26 | (10.83, 15.78) | 10.54 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 50 | high level of education | Male | 11.70 | 0.67 | (10.39, 13.02) | 17.45 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 100 | high level of education | Male | 12.43 | 1.24 | (10.00, 14.87) | 10.01 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 50 | low level of education | Female | 11.99 | 0.33 | (11.35, 12.63) | 36.73 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 100 | low level of education | Female | 11.72 | 0.48 | (10.79, 12.66) | 24.61 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 50 | intermediate level of education | Female | 12.09 | 0.21 | (11.69, 12.50) | 58.05 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 100 | intermediate level of education | Female | 12.91 | 0.35 | (12.23, 13.60) | 37.19 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 50 | high level of education | Female | 12.84 | 0.42 | (12.01, 13.67) | 30.36 | + +---------+---------------------------------+---------+-------+------+----------------+--------+ + | 100 | high level of education | Female | 13.21 | 0.84 | (11.56, 14.85) | 15.75 | + +=========+=================================+=========+=======+======+================+========+ + | Variable predicted: neg_c_7
Predictors modulated: c12hour = c(50, 100), c172code, | + | c161sex
Predictors averaged: barthtot (65) | + +=========+=================================+=========+=======+======+================+========+ + Table: Estimated Marginal Means + +# estimate_contrasts - by with special character + + Code + print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects", + p_adjust = "holm"), table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p + -------------------------------------------------------------------------------- + mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999 + high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999 + high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999 + mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999 + high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.565 + high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.691 + mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999 + high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.368 + high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999 + + Variable predicted: neg_c_7 + Predictors contrasted: c172code + p-value adjustment method: Holm (1979) + +--- + + Code + print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects", + p_adjust = "holm"), table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(810) | p + ---------------------------------------------------------------------------------- + low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 + low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001 + mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | > .999 + mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001 + mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001 + high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | > .999 + high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.099 + high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001 + low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 + mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001 + mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | > .999 + mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | 0.001 + high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001 + high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.636 + high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | > .999 + mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001 + mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001 + mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | > .999 + high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001 + high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001 + high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.450 + mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 + mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001 + high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | > .999 + high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.099 + high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001 + mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 + high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001 + high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.789 + high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.545 + high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001 + high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001 + high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | > .999 + high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 + high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001 + high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 + + Variable predicted: neg_c_7 + Predictors contrasted: c172code, barthtot = [sd] + p-value adjustment method: Holm (1979) + +--- + + Code + print(estimate_contrasts(fit, "c172code", "barthtot = [sd]", backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | barthtot | Difference | SE | 95% CI | t(810) | p + ------------------------------------------------------------------------------- + mid | low | 35.19 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596 + high | low | 35.19 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691 + high | mid | 35.19 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360 + mid | low | 64.79 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589 + high | low | 64.79 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071 + high | mid | 64.79 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099 + mid | low | 94.40 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221 + high | low | 94.40 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041 + high | mid | 94.40 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181 + + Variable predicted: neg_c_7 + Predictors contrasted: c172code + p-values are uncorrected. + +--- + + Code + print(estimate_contrasts(fit, c("c172code", "barthtot = [sd]"), backend = "marginaleffects"), + table_width = Inf, zap_small = TRUE) + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | SE | 95% CI | t(810) | p + ---------------------------------------------------------------------------------- + low, 64.792 | low, 35.188 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 + low, 94.396 | low, 35.188 | -3.85 | 0.54 | [-4.90, -2.80] | -7.20 | < .001 + mid, 35.188 | low, 35.188 | -0.22 | 0.42 | [-1.05, 0.60] | -0.53 | 0.596 + mid, 64.792 | low, 35.188 | -1.76 | 0.39 | [-2.52, -0.99] | -4.52 | < .001 + mid, 94.396 | low, 35.188 | -3.29 | 0.42 | [-4.11, -2.47] | -7.90 | < .001 + high, 35.188 | low, 35.188 | 0.22 | 0.56 | [-0.87, 1.31] | 0.40 | 0.691 + high, 64.792 | low, 35.188 | -1.21 | 0.46 | [-2.11, -0.31] | -2.65 | 0.008 + high, 94.396 | low, 35.188 | -2.64 | 0.56 | [-3.74, -1.55] | -4.73 | < .001 + low, 94.396 | low, 64.792 | -1.93 | 0.27 | [-2.45, -1.40] | -7.20 | < .001 + mid, 35.188 | low, 64.792 | 1.70 | 0.35 | [ 1.01, 2.40] | 4.81 | < .001 + mid, 64.792 | low, 64.792 | 0.17 | 0.31 | [-0.45, 0.79] | 0.54 | 0.589 + mid, 94.396 | low, 64.792 | -1.36 | 0.35 | [-2.04, -0.68] | -3.93 | < .001 + high, 35.188 | low, 64.792 | 2.15 | 0.51 | [ 1.15, 3.14] | 4.24 | < .001 + high, 64.792 | low, 64.792 | 0.72 | 0.40 | [-0.06, 1.49] | 1.81 | 0.071 + high, 94.396 | low, 64.792 | -0.72 | 0.51 | [-1.71, 0.28] | -1.41 | 0.160 + mid, 35.188 | low, 94.396 | 3.63 | 0.46 | [ 2.72, 4.54] | 7.81 | < .001 + mid, 64.792 | low, 94.396 | 2.10 | 0.43 | [ 1.24, 2.95] | 4.82 | < .001 + mid, 94.396 | low, 94.396 | 0.56 | 0.46 | [-0.34, 1.47] | 1.23 | 0.221 + high, 35.188 | low, 94.396 | 4.07 | 0.59 | [ 2.92, 5.23] | 6.91 | < .001 + high, 64.792 | low, 94.396 | 2.64 | 0.50 | [ 1.67, 3.62] | 5.32 | < .001 + high, 94.396 | low, 94.396 | 1.21 | 0.59 | [ 0.05, 2.37] | 2.05 | 0.041 + mid, 64.792 | mid, 35.188 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 + mid, 94.396 | mid, 35.188 | -3.07 | 0.31 | [-3.68, -2.45] | -9.80 | < .001 + high, 35.188 | mid, 35.188 | 0.45 | 0.49 | [-0.51, 1.40] | 0.92 | 0.360 + high, 64.792 | mid, 35.188 | -0.99 | 0.37 | [-1.71, -0.26] | -2.67 | 0.008 + high, 94.396 | mid, 35.188 | -2.42 | 0.49 | [-3.38, -1.46] | -4.95 | < .001 + mid, 94.396 | mid, 64.792 | -1.53 | 0.16 | [-1.84, -1.23] | -9.80 | < .001 + high, 35.188 | mid, 64.792 | 1.98 | 0.46 | [ 1.08, 2.88] | 4.32 | < .001 + high, 64.792 | mid, 64.792 | 0.55 | 0.33 | [-0.10, 1.19] | 1.65 | 0.099 + high, 94.396 | mid, 64.792 | -0.89 | 0.46 | [-1.79, 0.02] | -1.93 | 0.055 + high, 35.188 | mid, 94.396 | 3.51 | 0.48 | [ 2.57, 4.46] | 7.30 | < .001 + high, 64.792 | mid, 94.396 | 2.08 | 0.36 | [ 1.37, 2.79] | 5.74 | < .001 + high, 94.396 | mid, 94.396 | 0.65 | 0.48 | [-0.30, 1.60] | 1.34 | 0.181 + high, 64.792 | high, 35.188 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 + high, 94.396 | high, 35.188 | -2.86 | 0.64 | [-4.11, -1.61] | -4.50 | < .001 + high, 94.396 | high, 64.792 | -1.43 | 0.32 | [-2.06, -0.81] | -4.50 | < .001 + + Variable predicted: neg_c_7 + Predictors contrasted: c172code, barthtot = [sd] + p-values are uncorrected. + +# estimate_means - by is list + + Code + print(estimate_means(fit, list(c172code = c("low", "high"), c161sex = c( + "Female", "Male")), backend = "marginaleffects"), table_width = Inf, + zap_small = TRUE) + Output + Estimated Marginal Means + + c172code | c161sex | Mean | SE | 95% CI | t(825) + ----------------------------------------------------------- + low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44 + high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31 + low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25 + high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45 + + Variable predicted: neg_c_7 + Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male') + Predictors averaged: e16sex + +--- + + Code + print(estimate_means(fit, c("c172code = c('low', 'high')", + "c161sex = c('Female', 'Male')"), backend = "marginaleffects"), table_width = Inf, + zap_small = TRUE) + Output + Estimated Marginal Means + + c172code | c161sex | Mean | SE | 95% CI | t(825) + ----------------------------------------------------------- + low | Female | 12.13 | 0.33 | [11.48, 12.78] | 36.44 + high | Female | 12.73 | 0.38 | [11.98, 13.48] | 33.31 + low | Male | 11.09 | 0.61 | [ 9.89, 12.28] | 18.25 + high | Male | 11.77 | 0.58 | [10.64, 12.90] | 20.45 + + Variable predicted: neg_c_7 + Predictors modulated: c172code = c('low', 'high'), c161sex = c('Female', 'Male') + Predictors averaged: e16sex + +# estimate_epectation - don't print empty RE columns + + Code + print(estimate_expectation(m, by = "spp", predict = "conditional"), zap_small = TRUE) + Output + Model-based Predictions + + spp | Predicted | SE | CI + --------------------------------------- + GP | 0.73 | 0.21 | [0.32, 1.14] + PR | 0.42 | 0.16 | [0.11, 0.72] + DM | 0.94 | 0.25 | [0.45, 1.43] + EC-A | 0.60 | 0.19 | [0.24, 0.96] + EC-L | 1.42 | 0.37 | [0.69, 2.14] + DES-L | 1.34 | 0.36 | [0.63, 2.04] + DF | 0.78 | 0.21 | [0.37, 1.19] + + Variable predicted: count + Predictors modulated: spp + Predictors controlled: mined (yes) + Predictions are on the conditional-scale. + +# print - layouts and include data grid + + Code + print(out) + Output + Estimated Marginal Means + + Species | Mean | SE | 95% CI | t(147) + ------------------------------------------------ + setosa | 1.46 | 0.06 | [1.34, 1.58] | 24.02 + versicolor | 4.26 | 0.06 | [4.14, 4.38] | 70.00 + virginica | 5.55 | 0.06 | [5.43, 5.67] | 91.23 + + Variable predicted: Petal.Length + Predictors modulated: Species + +--- + + Code + print(out, select = "minimal") + Output + Estimated Marginal Means + + Species | Mean (CI) + ------------------------------ + setosa | 1.46 (1.34, 1.58) + versicolor | 4.26 (4.14, 4.38) + virginica | 5.55 (5.43, 5.67) + + Variable predicted: Petal.Length + Predictors modulated: Species + +--- + + Code + print(out, select = "minimal") + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference (CI) | p + ---------------------------------------------------- + versicolor | setosa | 2.80 (2.63, 2.97) | <0.001 + virginica | setosa | 4.09 (3.92, 4.26) | <0.001 + virginica | versicolor | 1.29 (1.12, 1.46) | <0.001 + + Variable predicted: Petal.Length + Predictors contrasted: Species + p-values are uncorrected. + +--- + + Code + print(out, select = "{estimate}{stars}|{ci}") + Output + Marginal Contrasts Analysis + + Level1 | Level2 | Difference | CI + ------------------------------------------------- + versicolor | setosa | 2.80*** | 2.63, 2.97 + virginica | setosa | 4.09*** | 3.92, 4.26 + virginica | versicolor | 1.29*** | 1.12, 1.46 + + Variable predicted: Petal.Length + Predictors contrasted: Species + p-values are uncorrected. + +--- + + Code + print(estimate_relation(m, by = "qsec")) + Output + Model-based Predictions + + qsec | Predicted | SE | 95% CI + --------------------------------------- + 14.50 | 2.80 | 0.19 | [2.41, 3.18] + 15.43 | 2.91 | 0.15 | [2.62, 3.21] + 16.37 | 3.03 | 0.11 | [2.81, 3.26] + 17.30 | 3.15 | 0.09 | [2.97, 3.32] + 18.23 | 3.27 | 0.08 | [3.10, 3.44] + 19.17 | 3.38 | 0.10 | [3.17, 3.60] + 20.10 | 3.50 | 0.14 | [3.21, 3.78] + 21.03 | 3.62 | 0.18 | [3.25, 3.98] + 21.97 | 3.73 | 0.22 | [3.28, 4.19] + 22.90 | 3.85 | 0.27 | [3.30, 4.40] + + Variable predicted: wt + Predictors modulated: qsec + Predictors controlled: mpg (20) + +--- + + Code + print(estimate_relation(m, by = "qsec"), include_grid = TRUE) + Output + Model-based Predictions + + qsec | mpg | Predicted | SE | 95% CI + ----------------------------------------------- + 14.50 | 20.09 | 2.80 | 0.19 | [2.41, 3.18] + 15.43 | 20.09 | 2.91 | 0.15 | [2.62, 3.21] + 16.37 | 20.09 | 3.03 | 0.11 | [2.81, 3.26] + 17.30 | 20.09 | 3.15 | 0.09 | [2.97, 3.32] + 18.23 | 20.09 | 3.27 | 0.08 | [3.10, 3.44] + 19.17 | 20.09 | 3.38 | 0.10 | [3.17, 3.60] + 20.10 | 20.09 | 3.50 | 0.14 | [3.21, 3.78] + 21.03 | 20.09 | 3.62 | 0.18 | [3.25, 3.98] + 21.97 | 20.09 | 3.73 | 0.22 | [3.28, 4.19] + 22.90 | 20.09 | 3.85 | 0.27 | [3.30, 4.40] + + Variable predicted: wt + Predictors modulated: qsec + Predictors controlled: mpg (20) + diff --git a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-1.svg b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-1.svg new file mode 100644 index 000000000..2b55f2cab --- /dev/null +++ b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-1.svg @@ -0,0 +1,384 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +0 +10 +20 +30 +40 +50 + + + + + + + + + +8 +10 +12 +x +Mean of y + +z + + + + + + + + + + + + +-1.09 +-0.06 +0.98 +plot-show_residuals-1 + + diff --git a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-2.svg b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-2.svg new file mode 100644 index 000000000..b39dc5bd1 --- /dev/null +++ b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-2.svg @@ -0,0 +1,407 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +0 +10 +20 +30 +40 +50 + + + + + + + + + +8 +10 +12 +x +Mean of y + +z + + + + + + + +-2 +0 +2 +plot-show_residuals-2 + + diff --git a/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-3.svg b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-3.svg new file mode 100644 index 000000000..acc3e64be --- /dev/null +++ b/tests/testthat/_snaps/residualize_over_grid/plot-show-residuals-3.svg @@ -0,0 +1,238 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +4 +5 +6 +7 +8 + + + + + + + + + + + +2.0 +2.5 +3.0 +3.5 +4.0 +4.5 +Sepal.Width +Mean of Sepal.Length + +Species + + + + + + + + + + + + +setosa +versicolor +virginica +plot-show_residuals-3 + + diff --git a/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md b/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md index 8d63eb2df..e8c7718b7 100644 --- a/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md +++ b/tests/testthat/_snaps/windows/estimate_contrasts_counterfactual.md @@ -9,7 +9,7 @@ --------------------------------------------------------------------------------- post | pre | control | 1.85 | 1.22 | [-0.53, 4.23] | 1.52 | 0.128 end | pre | control | 0.86 | 1.21 | [-1.51, 3.24] | 0.71 | 0.477 - end | post | control | -0.99 | 1.22 | [-3.37, 1.40] | -0.81 | 0.417 + end | post | control | -0.99 | 1.22 | [-3.37, 1.39] | -0.81 | 0.417 post | pre | tx | 6.57 | 1.57 | [ 3.50, 9.65] | 4.19 | < .001 end | pre | tx | 17.26 | 1.57 | [14.18, 20.34] | 10.99 | < .001 end | post | tx | 10.69 | 1.57 | [ 7.62, 13.76] | 6.82 | < .001 From 5e5985113d656c3faf12d2fa7877e25f1d920d02 Mon Sep 17 00:00:00 2001 From: etiennebacher Date: Tue, 17 Feb 2026 19:28:52 +0100 Subject: [PATCH 4/5] force testthat 3.3.1 --- DESCRIPTION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 5169946ed..910dd2b0c 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -101,7 +101,7 @@ Suggests: scales, see (>= 0.11.0), survival, - testthat (>= 3.2.1), + testthat (== 3.3.1), tinyplot (>= 0.6.0), tinytable, vdiffr, From aa80f174b872f82b06be27a8384c71ee1e34af5b Mon Sep 17 00:00:00 2001 From: etiennebacher Date: Tue, 17 Feb 2026 19:31:49 +0100 Subject: [PATCH 5/5] maybe <= 3.3.1 ? --- DESCRIPTION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 910dd2b0c..f77913c52 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -101,7 +101,7 @@ Suggests: scales, see (>= 0.11.0), survival, - testthat (== 3.3.1), + testthat (<= 3.3.1), tinyplot (>= 0.6.0), tinytable, vdiffr,