GROUP-LEVEL META-ANALYSES: AN EXAMINATION OF THE EFFECTS OF CHARACTERISTICS OF GROUP-LEVEL STUDIES ON THE ACCURACY OF PARAMETER ESTIMATES

This dissertation was an empirical investigation of how statistical artifacts and characteristics of group-level studies affect meta-analytic parameter estimates in group-level meta-analyses. Simulation procedures were employed to examine how the proportion of available group-level reliability information, the number of studies in a meta-analysis, and the type of group-level reliability estimate affect the accuracy of estimates of the mean and variance of rho when these population values are known. Archival data was used to identify known population parameter values and create group-level meta-analytic conditions commonly seen in the organizational sciences literature. This study has resulted in the following conclusions. When proportions of sample-based reliability are reduced in availability, meta-analyses are relatively accurate in estimating the magnitude of mean rho. As more studies enter meta-analyses, standard errors of mean rho are substantially reduced and confidence bands become increasingly smaller in width and this pattern of results holds regardless of the group-level reliability estimate used to individually correct correlations. Further, when meta-analyses involved the use of completely assumed values, the degree of accuracy in mirroring known population parameters was dependent on the degree to which the group-level reliability value approximates that of the population. Finally, both ICC(2) values and rCG group-based reliability estimates produced relatively accurate meta-analytic findings relative to their respective known population parameter values. Advantages and limitations to the use of each type of reliability estimate are discussed in detail in the manuscript.Ph.D. in Psychology, May 201