<Denis.Aydin <at> unibas.ch> writes: > I have a question regarding an output of a binomial lmer-model. > The model is as follows: > lmer(y~diet * day * female + (day|female),family=binomial)
A reproducible example would always be nice. > The corresponding output is: > Generalized linear mixed model fit by the Laplace approximation > Formula: y ~ diet * day * female + (day | female) > AIC BIC logLik deviance > 1084 1136 -531.1 1062 [ snip ] > Fixed effects: > Estimate Std. Error z value Pr(>|z|) > (Intercept) 0.996444 0.713703 1.396 0.1627 > dietNAA 1.194581 0.862294 1.385 0.1659 > day 0.142026 0.074270 1.912 0.0558 . > female 0.015629 0.019156 0.816 0.4146 > dietNAA:day -0.124755 0.088684 -1.407 0.1595 > dietNAA:female -0.024733 0.026947 -0.918 0.3587 > day:female -0.001535 0.001966 -0.781 0.4348 > dietNAA:day:female 0.001543 0.002720 0.568 0.5704 > > Now from my understanding, the estimates represent differences in slopes > and intercepts between different levels of "diet" and so on. > > My questions: > > 1. Is there a way to display the coefficients for all levels of variables > (e.g., "dietAA" and "dietNAA")? Because it is quite hard to calculate the > slopes and intercepts for all levels of each variable. See if lmer(y~(diet-1) * (day-1) * (female-1) + (day|female),family=binomial) helps, or see if you can use predict() with an appropriately constructed prediction data frame -- although not sure if predict works with GLMMs in current version of lme4. > > 2. Is there a way to get the degrees of freedom? Giant can of worms, I'm afraid. See <http://glmm.wikidot.com/faq> for relevant links and alternatives. ______________________________________________ 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.
