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/
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