Partialing out the effect of a covariable in a Poisson GLMM
On 13-01-21 02:51 AM, v_coudrain at voila.fr wrote:
Ben Bolker writes:
Don't know exactly what you want to do, but presumably fitting a "null model" with the covariate and then building more complex models on top of this -- adding the other covariates -- and doing sequential testing (anova(full_model,model_with_only_first_covariate)). The linear models idea of partialing out one variable and running a model on the residuals doesn't work as well, unfortunately.
Oh yes, thank you I can do it this way. Sould I turn REML to FALSE for model comparison? Best, Val?rie
REML is *ignored* when running glmer() [or lmer() with a 'family' argument]; as discussed at http://glmm.wikidot.com/faq , REML is somewhat poorly defined for GLMMs. (The development version of lme4 at least warns that the REML argument is ignored; the CRAN version just silently ignores it.) Ben Bolker