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In linear models and particularly in ANOVA, a contrast is a linear combination of parameters with coefficients summing up to zero. It is used to test the corresponding null hypothesis. Contrasts are especially often used with categorical predictors (factors) to make comparisons among the groups (categories). [See also tag 'categorical-encoding']
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R: emtrends pairwise contrast results change when testing slopes against 0 or 1
trds0<-emtrends(mod, pairwise ~ condition, var = "baseline", infer=TRUE) # or
trds0<-emtrends(mod, pairwise ~ condition, var = "baseline") |> test(null=0)
Cond=condition, CovBLCen =baseline
In trds0$contrasts … condition 0 is not significant.
trds1<-emtrends(mod, pairwise ~ condition, var = "baseline") |> test(null=1)
Cond=condition, CovBLCen =baseline
Unexpectedly, I found that the pairwise comparisons (trds1$contrasts …