[Q] Linear mixed models

[u/Trutzker]

Hello,

I have a question about LMMs:

Repeated-measures design, 2x2:
One continuous dependent variable
Two independent variables, each with two levels

I want to test for interaction; the hypothesis is directional.

First, a linear mixed model was estimated in R wirh lme:
AV ~ UV1 * UV2 + (1l Participant)

Then a Type 3 ANOVA with lmertest

And finally, using emmeans, simple contrasts and a planned directed interaction contrast

My question: In a 2x2 design, is it even necessary to run a Type 3 ANOVA after the LMM?

And is the planned directed interaction contrast even necessary?

I’m also confused by the fact that some people report LMM results in the text using b, while others use F.

I’d appreciate any answers.

[u/STATASUCKSBRO]

In a 2 by 2, the interaction is one degree of freedom. If the planned contrast is exactly the difference in differences you care about, the Type III interaction test is mostly a two sided duplicate. A directional test only makes sense if that direction was fixed before seeing the estimates.

[u/SalvatoreEggplant]

You aren't required to do any analysis that you're not interested in the results. If you don't care about the Anova table results, you don't have to ask for them. Or if you do ask for them, you don't have to look at them.

Typically, though, for post-hoc contrasts, these aren't typically done unless the relevant effect from the anova table is significant. However, this isn't necessarily a statistical requirement. You might get some raised eyebrows if you don't include the omnibus anova step in the results. But, honestly, if you are just interested in a specific contrast, you can just do that.

I assume you're asking about some results using t tests and some using F tests ? They might actually use chi-square tests. The upshot is that different functions will use different methods, and it doesn't really matter as long as you trust the methodology used in the function.