Hello R list, I am hoping to conduct a logistic regression with repeated measures, and would love an actual "code run through" for such an analysis. I found only one related post on this list, but a full answer was never provided. I understand that the routine lmer (or lmer2) in the lme4 package is often recommended in such a case, but actually implementing it is where I've hit a wall.
In a nutshell, the experiment involved presenting females from two groups (treatment, control) with an opportunity to mate with a virgin male every 6 hours for 48 hours. Every female was presented this opportunity at every time step (i.e., whether or not she mated at 6 hr, she was again presented with a male at 12 hr, and so on). In addition to which group a female belongs to, we have an a priori reason to want to test the effect of her initial body mass as a covariate. A subset of the data looks like this: female group mass time mate 1 control 5.7 0 1 1 control 5.7 6 1 1 control 5.7 12 0 1 control 5.7 18 0 1 control 5.7 24 0 1 control 5.7 30 1 1 control 5.7 36 0 1 control 5.7 42 1 1 control 5.7 48 0 2 treatm 5.3 0 1 2 treatm 5.3 6 0 2 treatm 5.3 12 0 2 treatm 5.3 18 0 2 treatm 5.3 24 0 2 treatm 5.3 30 1 2 treatm 5.3 36 0 2 treatm 5.3 42 0 2 treatm 5.3 48 0 3 control 6.1 0 1 3 control 6.1 6 0 3 control 6.1 12 0 3 control 6.1 18 0 3 control 6.1 24 1 3 control 6.1 30 1 3 control 6.1 36 0 3 control 6.1 42 1 3 control 6.1 48 0 ... How, then, to determine whether treatment females display different mating patterns over time than control females? Here's my crack at it: foo1 <- lmer2(mate ~ group * mass * time + (time | female), family=binomial) Thanks in advance, Steve ______________________________________________ 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.
