Overview of Meta-Analysis, Part 4 (of 7): Data Exploration
Posted: March 28, 2012 | Author: A. R. Hafdahl | Filed under: Overview of Meta-Analysis | Tags: coding, data management, effect size, meta-analysis, missing data, moderator, outlier, reporting guidance, sample size, significance testing | 1 CommentThis seven-part overview’s first three parts focused on collecting data used in meta-analyses: estimates of effect size (ES), sample sizes or conditional variances (CVs) to quantify ES sampling error or (im)precision, and ES features. The overview’s subsequent four parts address analyzing these data and presenting results. In this fourth part I begin by describing preliminary analyses that can help identify errors and issues to attend to in primary analyses. (Part 1 of this overview lists the topics for all seven parts.)
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Overview of Meta-Analysis, Part 2 (of 7): Sampling Error
Posted: March 11, 2012 | Author: A. R. Hafdahl | Filed under: Overview of Meta-Analysis | Tags: binary outcome, conditional variance, correlation, dependence, effect size, heterogeneity, meta-analysis, missing data, multivariate effect size, primary-study design, sample size, standardized mean difference | Leave a commentIn Part 1 of this seven-part overview of meta-analysis, I introduced Conn, Hafdahl, Cooper, Brown, and Lusk’s (2009) quantitative review of workplace exercise interventions and discussed extracting effect-size (ES) estimates. Building on that material, in this second part I’ll address obtaining info about an ES’s sampling error, which plays a critical role in most modern meta-analytic methods. (Part 1 of this overview lists topics in the subsequent five posts.)
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Meta-Analysis Sandwich 