Diane Srivastava <srivast <at> zoology.ubc.ca> writes: > I have a meta-analysis dataset which I would like to analyze as a mixed > model, where the y-variable is a measure of effect size, the random effect > is the study from which the effect size was extracted, and the fixed > effect is a categorical explanatory variable. The complication is that we > often have multiple estimates of effect size from a single study (e.g. the > experiment was repeated in different years, or under different > conditions). Being a meta-analysis, I need to weight the effect sizes by > the inverse of the effect SE. Thus my dataset includes: study, effect > size, SE, explanatory variables.
Andrew Gelman shows in several places (his books, R2WinBUGS package) how to use data (your effect size estimates) from previous analyses. He has mean and variance of the estimate (the data) and models them. The key is that you will have to swicth to BUGS. It has very flexible model language! Regards, Gregor ______________________________________________ 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.