Meta-analysis of proportions is conceptually simple: Faced with a binary outcome in multiple studies, we seek inference on some overall proportion of successes/failures. Under common effect models, exact inference has long been available, but is not when we more realistically allow for heterogeneity of the proportions. Instead a wide range of…

Meta-regression analyses usually focus on estimating and testing differences in average effect sizes between individual levels of each meta-regression covariate in turn. These metrics are useful but have limitations: they consider each covariate individually, rather than in combination, and they characterize only the mean of a potentially…

Tolerance intervals provide a bracket intended to contain a percentage (e.g., 80%) of a population distribution given sample estimates of the mean and variance. In random-effects meta-analysis, tolerance intervals should contain researcher-specified proportions of underlying population effect sizes. Using Monte Carlo simulation, we investigated…

This study describes a close replication of Friedrich, Buday, and Kerr's late 1990s survey of statistics instruction in undergraduate psychology programs. Disciplinary reform efforts at that time such as the report of the APA Task Force on Statistical Inference, together with recent progress in the "new statistics" movement, raise…

When cluster randomized experiments are analyzed as if units were independent, test statistics for treatment effects can be anticonservative. Hedges proposed a correction for such tests by scaling them to control their Type I error rate. This article generalizes the Hedges correction from a posttest-only experimental design to more common designs…

A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect…

Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…

Meta-analysis is a frequent tool among education and behavioral researchers to combine results from multiple experiments to arrive at a clear understanding of some effect of interest. One of the traditional assumptions in a meta-analysis is the independence of the effect sizes from the studies under consideration. This article presents a…

The use of measures of magnitude of effect has been advocated as a way to go beyond statistical tests of significance and to identify effects of a practical size. They have been used in meta-analysis to combine results of different studies. Describes problems associated with measures of magnitude of effect (particularly study size) and…

Putative ethnic group differences in various forms of psychopathology may have important theoretical, clinical, and policy implications. Recently, it has been argued that individuals of African descent are more likely to be psychopathic than those of European descent (R. Lynn, 2002). Preliminary evidence from the Psychopathy Checklist: Youth…

Possible relationships between five test examiner characteristics (gender, race, tenure, experience as a test administrator, and experience as a test developer or scorer) and six student achievement scores (reading, writing, language usage, mathematics, science, and social studies) were studied at the school level in a statewide assessment. The…