Hello, I posted a question yesterday but I got no replies, so I'll try to reformulate it in a more concise way.
I have the following data, summarizing approval ratings on two different surveys for a random sample of 1600 individuals: > ## Example: Ratings of prime minister (Agresti, Table 12.1, p.494) > rating <- matrix(c(794, 86, 150, 570), 2, 2) > dimnames(rating) <- list(First = c("approve", "disapprove"), + Second = c("approve", "disapprove")) > rating Second First approve disapprove approve 794 150 disapprove 86 570 I would like to fit a logit model with approve/disapprove as response, survey (first/second) as a fixed effect, and subject as a random effect. 1) Is it possible to fit such a model directly using "lmer"? or 2) Should I unroll the table above into a dataframe containing also fictitious subject id's? If this is the case, what is a clean way of doing it? Thank you in advance, Giovanni Petris -- Giovanni Petris <[EMAIL PROTECTED]> Associate Professor Department of Mathematical Sciences University of Arkansas - Fayetteville, AR 72701 Ph: (479) 575-6324, 575-8630 (fax) http://definetti.uark.edu/~gpetris/ ______________________________________________ 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.