Hi, I run the following models:
1a. lmer(Y~X+(1|Subject),family=binomial(link="logit")) and 1b. lmer(Y~X+(1|Subject),family=binomial(link="logit"),method="PQL") Why does 1b produce results different from 1a? The reason why I am asking is that the help states that "PQL" is the default of GLMMs and 2. gamm(Y~X,family=binomial(link="logit"),random=list(Subject=~1)) The interesting thing about the example below is, that gamm is also supposed to fit by "PQL". Interestingly, however, the GAMM fit yields about the coefficient estimates of 1b. But the significance values of 1a. Any insight would be greatly appreciated. library(lme4) library(mgcv) Y=c(0,1,1,1,1,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,1) X=c(1,2,3,4,3,1,0,0,2,3,3,2,4,3,2,1,1,3,4,2,3) Subject=as.factor(c(1,2,3,4,5,6,7,1,2,3,4,5,6,7,1,2,3,4,5,6,7)) cbind(Y,X,Subject) r1=lmer(Y~X+(1|Subject),family=binomial(link="logit")) summary(r1) r2=lmer(Y~X+(1|Subject),family=binomial(link="logit"),method="PQL") summary(r2) r3=gamm(Y~X,family=binomial(link="logit"),random=list(Subject=~1)) summary(r3$gam) ------------------------- cuncta stricte discussurus ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
