Bayesian methods seem a natural choice for combining sources of evidence in meta-analyses. However, in practice, their sensitivity to the choice of prior distribution is much less attractive, particularly for parameters describing heterogeneity. A recent non-Bayesian approach to fixed-effects meta-analysis provides novel ways to think about…

Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…

Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

Single case designs are a set of research methods for evaluating treatment effects by assigning different treatments to the same individual and measuring outcomes over time and are used across fields such as behavior analysis, clinical psychology, special education, and medicine. Emerging standards for single case designs have focused attention on…

This conference presentation reviews the authors' work on autocorrelations in single-case designs. The bias-corrected autocorrelation is computed, results are meta-analyzed with 5-level multilevel analysis in SAS Proc Mixed. Results suggest autocorrelations are normally distributed, and that taking into account nesting in outcomes and articles…

Meta-analysis of research on a topic may exclude reports that do not present their results in a statistical form amendable to summarizing procedures used. This article illustrates how researchers can consider this aspect in computing statistics from their data. An illustration of how that can sometimes be done is presented. (Author/JAZ)

Validity generalization meta-analysis (VG) examines the extent to which the validity of an instrument can be transported across settings. VG offers correction and summarization procedures designed in part to remove the effects of statistical artifacts on estimates of association between criterion and predictor. By employing a random effects model,…