4 papers
Fitting Generalized Linear Mixed-Effects Models using lme4
Anna Ly, Rune Haubo Bojesen Christensen, Douglas Bates +2
The lme4 R package can be used to fit generalized linear mixed models (GLMMs), which extend the class of linear mixed models (LMMs). The two main extensions provided by GLMMs are (…
Too Few or Too Many? Sample Size Estimation for Differential Abundance Studies
Michael Agronah, Benjamin M. Bolker
Determining an appropriate sample size for a study is a crucial step in planning scientific research. Appropriate sample size planning avoids both inadequate and inflated sample si…
Meta-analysis with the glmmTMB R package
Coralie Williams, Maeve McGillycuddy, Mollie Brooks +6
Two common formulations of meta-analytical models include the standard two-stage normal-normal models, which synthesise estimated effect sizes, and the one-stage generalised linear…
Fitting Linear Mixed-Effects Models using lme4
Douglas Bates, Martin Mächler, Ben Bolker +1
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package…