title: Meta-analysis: an introduction using regression models.
abstract: Research synthesis of evaluation findings is a multistep process. An investigator identifies a research question, acquires the relevant literature, codes findings from that literature, and analyzes the coded data to estimate the average treatment effect and its distribution in a population of interest. The process of estimating the average treatment effect is meta-analysis. Meta-analysis is gaining popularity across the social sciences, but introductions and even advanced treatments of the subject are often formula-driven. Researchers, who apply formulas without understanding, risk both misapplication and misinterpretation. This article derives formulas used in meta-analysis using standard regression models so this article seeks to introduce readers with an understanding of regression analysis to meta-analysis, intending thereby to motivate and facilitate a deeper reading of the meta-analysis literature.
authors.affiliation: Abt Associates Inc., Cambridge, MA, USA. bill_rhodes@abtassoc.com
authors.forename: William
authors.initials: W
authors.lastname: Rhodes
mesh_terms: D015982:Bias; D035843:Biomedical Research / Q000379:methods*; D006801:Humans; D016015:Logistic Models; D015201:Meta-Analysis as Topic; D015588:Observer Variation; D015203:Reproducibility of Results