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Dear All, let E(Y | t, b, theta) be the conditional expectation of Y where b is a vector of random effects , theta is a vector of fixed effects and t is the time of observation (t =1,2, ...,n). I wonder if nlme has a function to compue E(Y | t, theta). I know that it can be done by approximating the integrals over b of E(Y | t, b, theta). But I am wondering if nlme has a function

Hi, I am using lmer (from the package lme4) to predict a binary response variable (REL) from a bunch of fixed effects and two random effects (Speaker_ID and NPhead_lemma): fit <- lmer(REL ~ SPEAKER_GENDER + log(SPEECHRATE) + SQSPEECHRATE + ..... + (1|Speaker_ID) + (1|NPhead_lemma), family="binomial", data=data.lmer, method="Laplace", model=T, x=T) I