Findings show that one of the central problems facing meta-analysts is missing data. Various statistical techniques have been developed to deal with this problem in the context of effect size calculation in particular, adjusting error variance estimates upward to account for potential “null model” studies that failed to make it in to the meta-analyst’s sample. What has not been forthcoming so far is equal attention focused on systematic methods for locating missing data regarding program characteristics from the studies included in a meta-analysis, as opposed to merely re-estimating the standard errors under the false assumption that such information is either unobtainable or irrelevant. This study noted that scholars need to try harder to obtain more specific information regarding program characteristics/integrity when conducting a meta-analysis on correctional treatment effectiveness; this would aid considerably in efforts to produce unambiguous conclusions concerning efficacy in correctional treatment. Notes and references