Code
print(estimate_contrasts(model, contrast = c("three", "vs", "am"), backend = "marginaleffects"),
digits = 1, zap_small = TRUE, table_width = Inf)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(24) | p
----------------------------------------------------------------------------------------------
three 0, vs 0, am 1 | three 0, vs 0, am 0 | 2.9 | 2.2 | [ -1.8, 7.5] | 1.3 | 0.213
three 0, vs 1, am 0 | three 0, vs 0, am 0 | 5.8 | 2.5 | [ 0.8, 10.9] | 2.4 | 0.026
three 0, vs 1, am 1 | three 0, vs 0, am 0 | 14.0 | 2.1 | [ 9.7, 18.4] | 6.7 | < .001
three 1, vs 0, am 0 | three 0, vs 0, am 0 | -0.6 | 2.0 | [ -4.7, 3.6] | -0.3 | 0.780
three 1, vs 0, am 1 | three 0, vs 0, am 0 | 7.5 | 2.8 | [ 1.7, 13.4] | 2.7 | 0.014
three 1, vs 1, am 0 | three 0, vs 0, am 0 | 5.1 | 2.2 | [ 0.5, 9.7] | 2.3 | 0.032
three 1, vs 1, am 1 | three 0, vs 0, am 0 | 10.6 | 2.8 | [ 4.7, 16.4] | 3.7 | 0.001
three 0, vs 1, am 0 | three 0, vs 0, am 1 | 3.0 | 2.7 | [ -2.5, 8.4] | 1.1 | 0.275
three 0, vs 1, am 1 | three 0, vs 0, am 1 | 11.2 | 2.3 | [ 6.4, 16.0] | 4.8 | < .001
three 1, vs 0, am 0 | three 0, vs 0, am 1 | -3.4 | 2.2 | [ -8.1, 1.2] | -1.5 | 0.139
three 1, vs 0, am 1 | three 0, vs 0, am 1 | 4.7 | 3.0 | [ -1.6, 10.9] | 1.5 | 0.135
three 1, vs 1, am 0 | three 0, vs 0, am 1 | 2.2 | 2.5 | [ -2.8, 7.3] | 0.9 | 0.374
three 1, vs 1, am 1 | three 0, vs 0, am 1 | 7.7 | 3.0 | [ 1.5, 13.9] | 2.6 | 0.017
three 0, vs 1, am 1 | three 0, vs 1, am 0 | 8.2 | 2.5 | [ 3.0, 13.4] | 3.2 | 0.004
three 1, vs 0, am 0 | three 0, vs 1, am 0 | -6.4 | 2.5 | [-11.5, -1.3] | -2.6 | 0.016
three 1, vs 0, am 1 | three 0, vs 1, am 0 | 1.7 | 3.2 | [ -4.9, 8.2] | 0.5 | 0.600
three 1, vs 1, am 0 | three 0, vs 1, am 0 | -0.7 | 2.7 | [ -6.2, 4.7] | -0.3 | 0.782
three 1, vs 1, am 1 | three 0, vs 1, am 0 | 4.7 | 3.2 | [ -1.8, 11.3] | 1.5 | 0.149
three 1, vs 0, am 0 | three 0, vs 1, am 1 | -14.6 | 2.1 | [-18.9, -10.3] | -6.9 | < .001
three 1, vs 0, am 1 | three 0, vs 1, am 1 | -6.5 | 2.9 | [-12.5, -0.5] | -2.2 | 0.035
three 1, vs 1, am 0 | three 0, vs 1, am 1 | -8.9 | 2.3 | [-13.7, -4.1] | -3.8 | < .001
three 1, vs 1, am 1 | three 0, vs 1, am 1 | -3.5 | 2.9 | [ -9.5, 2.5] | -1.2 | 0.246
three 1, vs 0, am 1 | three 1, vs 0, am 0 | 8.1 | 2.8 | [ 2.2, 13.9] | 2.8 | 0.009
three 1, vs 1, am 0 | three 1, vs 0, am 0 | 5.7 | 2.2 | [ 1.0, 10.3] | 2.5 | 0.019
three 1, vs 1, am 1 | three 1, vs 0, am 0 | 11.1 | 2.8 | [ 5.3, 17.0] | 3.9 | < .001
three 1, vs 1, am 0 | three 1, vs 0, am 1 | -2.4 | 3.0 | [ -8.6, 3.8] | -0.8 | 0.428
three 1, vs 1, am 1 | three 1, vs 0, am 1 | 3.1 | 3.5 | [ -4.1, 10.2] | 0.9 | 0.389
three 1, vs 1, am 1 | three 1, vs 1, am 0 | 5.5 | 3.0 | [ -0.7, 11.7] | 1.8 | 0.081
Variable predicted: mpg
Predictors contrasted: three, vs, am
p-values are uncorrected.
Code
print(estimate_contrasts(model, contrast = "am", backend = "marginaleffects"),
zap_small = TRUE, table_width = Inf)
Output
Marginal Contrasts Analysis
Level1 | Level2 | Difference | SE | 95% CI | t(24) | p
-------------------------------------------------------------------
1 | 0 | 6.15 | 1.34 | [3.40, 8.91] | 4.61 | < .001
Variable predicted: mpg
Predictors contrasted: am
Predictors averaged: three, vs
p-values are uncorrected.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.