I am running a LMM (using the lmer4 package) with the following structure: lmer(Response~F1+F2+F3+(1|R1)+(1|R1:T2)+(1|R2))

For my research question I would like to quantify how much of the overall variance is explained by each indvidual fixed and each random effect. In other words I would like to be able to say something like: xy% of the overall variance are explained by the fixed effect F1, yz% of the overall model variance are explained be the interaction of the random effects R1 and T2 etc. Is there an R-package that can use my lmer models and provide me with the individual variance proportions (or another measure of effect size) for each fixed and random effect? The fixed and random effect variances should be comparable

I looked up several posts on stackoverfolw:e.g. https://stats.stackexchange.com/que...f-explained-variance-in-a-mixed-effects-model

But in most cases the recommended packages can only proved overall variances across all fixed or random effects (e.g. the MuMIn package) or they provide either only random effect variances (e.g. the specr package) or only effect sizes for fixed effects (e.g. anova_stats)

Your help is much appreciated Mike