A general and simple method for obtaining R 2 from generalized linear mixed‐effects models

Summary The use of both linear and generalized linear mixed‐effects models ( LMM s and GLMM s) has become popular not only in social and medical sciences, but also in biological sciences, especially in the field of ecology and evolution. Information criteria, such as Akaike Information Criterion ( AIC ), are usually presented as model comparison tools for mixed‐effects models. The presentation of ‘variance explained’ ( R 2 ) as a relevant summarizing statistic of mixed‐effects models, however, is rare, even though R 2 is routinely reported for linear models ( LM s) and also generalized linear models ( GLM s). R 2 has the extremely useful property of providing an absolute value for the goodness‐of‐fit of a…

• DF
  Deutsche Forschungsgemeinschaft