If we start with a collection of independent effect size estimates, each estimate a corresponding effect size we can assume that where denotes the observed effect in the -th study, the corresponding (unknown) true effect, is the sampling error, and . Therefore, the ’s are assumed to be unbiased and normally distributed estimates of their corresponding true effects. The sampling variances (i.e., values) are assumed to be known.
If we start with a collection of independent effect size estimates, each estimate a corresponding effect size we can assume that where denotes the observed effect in the -th study, the corresponding (unknown) true effect, is the sampling error, and . Therefore, the ’s are assumed to be unbiased and normally distributed estimates of their corresponding true effects. The sampling variances (i.e, values) are assumed to be known.