Likelihood‐based inference for generalized linear mixed models: Inference with the R package glmm

The R package glmm enables likelihood‐based inference for generalized linear mixed models with a canonical link. No other publicly available software accurately conducts likelihood‐based inference for generalized linear mixed models with crossed random effects. glmm is able to do so by approximating the likelihood function and two derivatives using importance sampling. The importance sampling distribution is an essential piece of Monte Carlo...