The model R squared and semipartial R squared for the linear and generalized linear mixed model (LMM and GLMM) are computed with confidence limits. The R squared measure from Edwards et.al (2008) <DOI:10.1002/sim.3429> is extended to the GLMM using penalized quasilikelihood (PQL) estimation (see Jaeger et al. 2016 <DOI:10.1080/02664763.2016.1193725>). Three methods of computation are provided and described as follows. First, The KenwardRoger approach. Due to some inconsistency between the 'pbkrtest' package and the 'glmmPQL' function, the KenwardRoger approach in the 'r2glmm' package is limited to the LMM. Second, The method introduced by Nakagawa and Schielzeth (2013) <DOI:10.1111/j.2041210x.2012.00261.x> and later extended by Johnson (2014) <DOI:10.1111/2041210X.12225>. The 'r2glmm' package only computes marginal R squared for the LMM and does not generalize the statistic to the GLMM; however, confidence limits and semipartial R squared for fixed effects are useful additions. Lastly, an approach using standardized generalized variance (SGV) can be used for covariance model selection. Package installation instructions can be found in the readme file.
Package details 


Author  Byron Jaeger [aut, cre] 
Maintainer  Byron Jaeger <byron.jaeger@gmail.com> 
License  GPL2 
Version  0.1.2 
URL  https://github.com/bcjaeger/r2glmm 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.