Hello I'm very much a beginner on meta-analysis, so apologies if this is a trivial posting. I've been sent a set data from separate experimental studies, Treatment and Control, but no measure of the variance of effect sizes, numbers of replicates etc. Instead, for each study, all I have is the mean value for the treatment and control (but not the SD). As far as I can tell, this forces me into an unweighted meta-analysis, with all the caveats and dangers associated with it. Two possible approaches might be:
a) Take the ln(treatment/control) and perform a Fisher's randomisation test (and also calculate +/- CI). b) Regress the treatment vs control values, then randomise (with or without replacement?) individual values, comparing the true regression coefficient with the distribution of randomisation regression coefficients. Both approaches would appear to be fraught with risks; for example in the regression approach, it is probable that the error distribution of an individual randomised regression might not be normal - would this then invalidate the whole set of regressions? Many thanks for your advice. Roy -- Roy Sanderson Institute for Research on Environment and Sustainability (IRES) Devonshire Building Newcastle University Newcastle upon Tyne NE1 7RU [EMAIL PROTECTED] 0191 246 4835 ______________________________________________ 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.
