Hi Henrik,
I'm fairly new to mixed modelling, and I have a question regarding the output of afex::mixed() vs. glmer(), or more specifically the results of ANOVAs performed on them...
I'm modelling accuracy data in a within-Ss design with three factors, using afex I specify:
m1 <- afex::mixed( accuracy ~ x * y * z + ( 1 | subj ), method = 'LRT', family = binomial, data = dat)
and (eventually) using car:
m2 <- lme4::glmer( accuracy ~ x * y * z + ( 1 | subj ) , family = binomial, data = dat)
(I guess that bit was redundant...)
I get a discrepancy wherein if I run:
afex::nice(m1)
The effect of 'x' is reported as significant, but for:
afex::set_sum_contrasts()
car::Anova(m2)
The effect of 'x' doesn't even approached significance (according to the Chisq test)
Do the Chi-Square tests reported in both methods reflect the same thing? That is, the effect of 'x' on accuracy? Or are one of these methods testing something different?
Thank you,
Brett