Dear R-experts! I am currently running a meta-analysis with the help of the great metafor package. However I have some difficulties setting up my raw data to enter it to the meta-analysis models. I have a group of subjects that have been measured in two continuous variables (A & B). I have the information about the mean of the two variables, the group size (n) and the standard deviations of the two variables. Now I would like to average both variables (A & B) and get the mean and standard deviation of the merged variable (C). As for the mean this would be quiet easy: I would just take the mean of mean A and mean B to get the mean of C. However for the standard deviation this seems more tricky as it is to assume that standard deviations in A & B correlate. I assume (based on further analysis) a correlation of r =0.5. I found the formula to get the standard deviation of the SUM (not the mean) of two variables: SD=SQRT(SD_A^2 + SD_B^2 + 2*r*SD_A*SD_B)
with SD_B and SD_B being the standard deviation of A and B. And r*SD_A*SD_B being the covariance of A and B. Would this formula also be valid if I want to average (and not sum) my two variables? Many thanks for any help & best wishes, Jokel [[alternative HTML version deleted]] ______________________________________________ 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.