Suppose there are k independent studies and for each study the experimental and control groups have been sampled from independent but essentially arbitrary populations. The problem is to construct a plausible standard error of the effect size mean (effect sizes are standardized experimental-control group mean differences) when given only minimal sample statistic information. Standard errors based on the sample standard error, or bootstrap, will typically be much too large and have very large variance. A normal theory estimator may prove practically useful in more general settings. Asymptotic distribution-free estimators are provided for two cases.
