I have a longitudinal data set that contains a repeated measurement of the same participants over 6 different measurement times. I've built my model via lmer in r:
Model <- lmer(output ~ Fa + Yr + Yrs + Age + Hrs + (1|PartID) + (1|Scenario), data = data)
where the participant id is crossed with the repeated scenario.
I was able to calculate the F-stats and their associated significant levels for an omnibus test, but I need to assess which scenarios the Iv's best predict via a pairwise comparison.
Is there a way to do this under the framework of a repeated measure in lmer?
Additionally, my data is non-parametric and required a permutation of the F-statistics. Is there a method of also permutating the pairwise comparison t-statistics?