On Fri, May 02, 2008 at 03:06:31PM -0500, Giovanni Petris
wrote:>
> 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?
Unroll it.
Asking for a "clean" way to do something is a disincentive because it
implies that you know how to do it but not cleanly. In the future I
would suggest that you do one of two things
a) post your on dirty version and ask for a cleaner one, or
b) just ask for something that works.
Something like ...
ratings <-
data.frame(
response = c(
rep(c(1,1), 794),
rep(c(1,0), 150),
rep(c(0,1), 86),
rep(c(0,0), 570)),
time = rep(c(1,2), 1600),
subject=rep(1:1600, each=2))
test.lmer <- lmer(response ~ time + (1|subject), data=ratings,
family=binomial)
but I don't know if you think that's clean or not.
Andrew
> Thank you in advance,
> Giovanni Petris
>
> --
>
> Giovanni Petris <GPetris at uark.edu>
> 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 at 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.
--
Andrew Robinson
Department of Mathematics and Statistics Tel: +61-3-8344-6410
University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599
http://www.ms.unimelb.edu.au/~andrewpr
http://blogs.mbs.edu/fishing-in-the-bay/