I've built a multivariate linear mixed effect model with 3 dependent variables and a repeated measures factor. My data follows a hierarchical structure where participants are nested within groups.
my model is as follows:
model <- lmer(value ~ variable:Time -1 + (0 + variable | Group/Participant), data = Fixed_Data
I'm attempting to calculate the overall r-squared for this model, and have been following this post.
As such, i've used this code:
I'm a little iffy about this though, as I'm receiving an r-square of 90+%
To compare, I've calculated this multivariate analysis as three individual univariate analyses:
model1 <- lmer(DV1 ~ Time + (1|Group/Participant), data = Data) ...
When calculating the r-squared for these models, I'm getting r-squares of under 10% each.
Is the discrepancy between these r-square values normal? Is calculating an r-square for a multivariate linear mixed effect model possible?