In a classical meta analysis model y_i = X_i * beta_i + e_i, data {y_i} are assumed to be independent effect sizes. However, I'm encountering the following two scenarios:
(1) Each source has multiple effect sizes, thus {y_i} are not fully independent with each other. (2) Each source has multiple effect sizes, each of the effect size from a source can be categorized as one of a factor levels (e.g., happy, sad, and neutral). Maybe better denote the data as y_ij, effect size at the j-th level from the i-th source. I can code the levels with dummy variables into the X_i matrix, but apparently the data from the same source are correlated with each other. In this case, I would like to run a few tests one of which is, for example, whether there is any difference across all the levels of the factor. Can metafor handle these two cases? Thanks, Gang ______________________________________________ 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.