lmer and a response that is a proportion
Dear Cameron,
-----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Cameron Gillies Sent: Sunday, December 03, 2006 1:58 PM To: r-help at stat.math.ethz.ch Subject: [R] lmer and a response that is a proportion Greetings all, I am using lmer (lme4 package) to analyze data where the response is a proportion (0 to 1). It appears to work, but I am wondering if the analysis is treating the response appropriately - i.e. can lmer do this?
As far as I know, you can specify the response as a proportion, in which case the binomial counts would be given via the weights argument -- at least that's how it's done in glm(). An alternative that should be equivalent is to specify a two-column matrix with counts of "successes" and "failures" as the response. Simply giving the proportion of successes without the counts wouldn't be appropriate.
I have used both family=binomial and quasibinomial - is one more appropriate when the response is a proportion? The coefficient estimates are identical, but the standard errors are larger with family=binomial.
The difference is that in the binomial family the dispersion is fixed to 1, while in the quasibinomial family it is estimated as a free parameter. If the standard errors are larger with family=binomial, then that suggests that the data are underdispersed (relative to the binomial); if the difference is substantial -- the factor is just the square root of the estimated dispersion -- then the binomial model is probably not appropriate for the data. I hope this helps, John
Thanks very much for any insight you may have! Cam Cam Gillies PhD Candidate Biological Sciences University of Alberta
______________________________________________ R-help at stat.math.ethz.ch 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.