R square in mixed model with random effects

For mixed models with random intercepts only, the statistic for R square is

R2=(Vint onlyVfull model)/Vint only

My question is: How to estimate R square in mixed models with random effects? And estimate R square for each level? Let’s say it’s a 3-level model with random effects of time at level 2.


The R package MuMIn also now has a function for calculating Nakagawa and Schielzeth’s r-squared for mixed models. That is the function r.squaredGLMM() and you simply feed it a lmer object (from package lme4) to obtain the values.
MuMIn has excellent documentation so you should be able to learn any details there.

Source : Link , Question Author : NonSleeper , Answer Author : DirtStats

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