Extracting means and SE from lme & lmer with random terms
Julie Kern <juliekern27 at ...> writes:
Dear R gurus, I?ve done a lot of reading around this topic but can?t seem to find a solution that is working. I am running linear mixed models with lme & a few glmms with lmer (binomial response term). I would like to extract (not predict) the means & their SE of the fixed effects from the model but am having difficulties. For example, having run the model Vocalising<-lmer(Vocalsing~Sex+Age+Rank+fixef4...fixef7+(1|Group/ID), data=mydata, family=binomial, REML=FALSE) I would get a value for the mean proportion of males and females that vocalised during bouts as well as the standard error of the proportion.
Can you give us a (small!) reproducible example? Do you get the desired results (in terms of which values are computed) if you use glm() instead of lmer() and drop the random effects term? A couple of notes: * REML is silently ignored when fitting GLMMs (there is a bit of commentary on this in http://glmm.wikidot.com/faq ; the development version of lme4 produces a warning). * the CRAN version of lme4 silently passes control to glmer() when 'family' is specified, but it is probably better to call glmer() explicitly when doing GLMMs (the development version requires that you call glmer() explicitly).
I have tried using allEffects in the effects package but am only managing to get means. Is this because I have random terms in my model as well as fixed? If so how would you recommend I proceed? I have tried using attr(ranef(mymodel, postVar = TRUE)[[1]], "postVar")as recommended on http://glmm.wikidot.com/faq but this produces a list of 40 or so numbers so I?ve clearly misunderstood this!
the incantation you reproduce here is for getting the variances of the random effect 'estimates' (conditional modes), not for getting the standard errors of the fixed-effect parameters. Ben Bolker