Meta-analyses often include studies that report multiple effect sizes based on a common pool of subjects or that report effect sizes from several samples that were treated with very similar research protocols. The inclusion of such studies introduces dependence among the effect size estimates. When the number of studies is large, robust variance…

In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…

Monte Carlo studies of several fixed-effects methods for combining and comparing correlation matrices have shown that two refinements improve estimation and inference substantially. With rare exception, however, these simulations have involved homogeneous data analyzed using conditional meta-analytic procedures. The present study builds on…

A selection model for meta-analysis is proposed that models the selection process and corrects for the consequences of selection by publication on estimates of the mean and variance of the effect parameters. Simulation studies show that the model substantially reduces bias when the model specification is correct. (SLD)

Two new methods of estimating the mean population correlation (M) and the standard deviation of population correlations (SD) were suggested and tested by Monte Carlo simulations. Results show no consistent advantage to using the Pearson correlation or Fisher's Z in estimating M or SD; estimates from all methods are similar. (SLD)