Looks like the center effect improves overall accuracy while being independent of the other terms.
A few things to try Compare coef(model.fix) to fixef(model.rand). Add center as a fixed effect to model .fix Try a conditional logit (clogit from survival) See how consistent the coefficients are On Sat, Jun 11, 2022 at 11:14 AM Frank S. <f_j_...@hotmail.com> wrote: > Dear R users, > > I'm analyzing a particular score "y" among several individuals, each of > which belongs to a center, a factor with three > different levels (3 possible centers). I have treated the "center" as a > fixed effect, and as a random term (package lme4): > > 1) model.fix <- glm(y ~ var.1 + var.2 + var.3 + var.4 + var.5 + center, > family = "binomial", data = dat) > 2) model.rand <- glmer(y ~ var.1 + var.2 + var.3 + var.4 + var.5 + (1 | > center), family = "binomial", data = dat) > > The issue is that both models provide exactly the same coefficients and > p-values for the 5 baseline variables, so I assumed > that it was due to the small number of levels (in fact, too few ). > However, when computing anova(model.rand, model.fix), > the output indicates a p-value < 0.001 in favour of the "model.rand". > What's happening? Should I take the random terms? > > Thanks for any help! > > Frank S. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. > -- Sent from Gmail Mobile [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.