Hi all! I am working with GLMM using the binomial family I use the following codes I dropped no significant terms, refitting the model and comparing the changes with likelihood: G.1<-lmer(data$Ymat~stu+spi+stu*sp1+(1|ber),data=data,family="binomial") G.1b<-lmer(data$Ymat~stu+spi+(1|ber),data=data,family="binomial") anova (G.1,G.2) But, when I want to evaluate the significance of random effect (1|ber) I cannot use a likelihood-ratio test, probably because the link function of both models is different. Can anyone help me? I recently started using GLM language R. Sorry if my terms are not adequate. Thanks!
Evaluating the significance of the random effects in GLMM
2 messages · Gabriela Agostini, Ben Bolker
Gabriela Agostini <gabrielaagostini18 at ...> writes:
Hi all! I am working with GLMM using the binomial family I use the following codes I dropped no significant terms, refitting the model and comparing the changes with likelihood: G.1<-lmer(data$Ymat~stu+spi+stu*sp1+(1|ber),data=data,family="binomial") G.1b<-lmer(data$Ymat~stu+spi+(1|ber),data=data,family="binomial") anova (G.1,G.2) But, when I want to evaluate the significance of random effect (1|ber) I cannot use a likelihood-ratio test, probably because the link function of both models is different.
Please don't cross-post between r-help and r-sig-mixed-models ... I gave a partial answer to your question on r-help ( http://article.gmane.org/gmane.comp.lang.r.general/285341 ) but indicated that we need more information before we can answer. Follow-up here, not on r-help. Ben Bolker