It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully 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 performing a meta-analysis unexplained variation above that predicted by within study variation is usually modeled by a random effect. However, in some cases, this is not sufficient to explain all the variation because of outlier or unusual studies. A previously described method is to define an outlier as a study requiring a higher random…

Researchers may have multiple motivations for combining disparate pieces of evidence in a meta-analysis, such as generalizing experimental results or increasing the power to detect an effect that a single study is not able to detect. However, while in meta-analysis, the main question may be simple, the structure of evidence available to answer it…

Three meta-analytic studies have shown that bilingual education is an effective method for teaching students who are English language learners. However, there is limited evidence of the effectiveness of bilingual education in preschool. This study used multiple years of data from the Manchester (New Hampshire) Even Start program and relevant…

The use of hierarchical models in social science research is discussed, with emphasis on causal inference and consideration of the limitations of hierarchical models. The increased use of Gibbs sampling and other Markov-chain Monte Carlo methods in the application of hierarchical models is recommended. (SLD)