Network meta-analysis is a popular method to synthesize the information obtained in a systematic review of studies (e.g., randomized clinical trials) involving subsets of multiple treatments of interest. The dominant method of analysis employs within-study information on treatment contrasts and integrates this over a network of studies. One…

This article reviews some of the strengths and limitations of the comparative use of meta-analysis findings, using examples from the Sutton Trust-Education Endowment Foundation Teaching and Learning "Toolkit" which summarizes a range of educational approaches to improve pupil attainment in schools. This comparative use of quantitative…

Inference ability is considered central to discourse processing and has been shown to be important across models of reading comprehension. To evaluate the impact of inference instruction, a meta-analysis of 25 inference studies in Grades K-12 was conducted. Results showed that inference instruction was effective for increasing students' general…

An integrative social identity model of collective action (SIMCA) is developed that incorporates 3 socio-psychological perspectives on collective action. Three meta-analyses synthesized a total of 182 effects of perceived injustice, efficacy, and identity on collective action (corresponding to these socio-psychological perspectives). Results…

There is general agreement that meta-analysis is an important tool for synthesizing study results in quantitative educational research. Yet, a shared feature of many meta-analyses is a failure to report sufficient information for readers to fully judge the reported findings, such as the populations to which generalizations are to be made,…

There has been significant interest in the role of anxiety sensitivity (AS) in the anxiety disorders. In this meta-analysis, we empirically evaluate differences in AS between anxiety disorders, mood disorders, and nonclinical controls. A total of 38 published studies (N = 20,146) were included in the analysis. The results yielded a large effect…

Two chapters of this issue consider critical multiplism as a research strategy with links to meta analysis and generalizability theory. The unifying perspective it can provide for quantitative and qualitative evaluation is discussed. The third chapter explores meta analysis as a way to improve causal inferences in nonexperimental data. (SLD)