Overview of Meta-Analysis, Part 4 (of 7): Data Exploration

This 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.)
Read the rest of this entry »


Overview of Meta-Analysis, Part 3 (of 7): Effect-Size Features

In Part 2 of this seven-part overview, I described obtaining the sample size(s) or conditional variance (CV) associated with an effect-size (ES) estimate to quantify this estimate’s sampling error or (im)precision.  Here in Part 3 I’ll address coding features linked to ESs.  Whereas this overview’s first three parts focus on collecting data used in a research synthesis, its subsequent four parts will address meta-analyzing these data and presenting results.  (Part 1 lists the topics for all seven parts.)
Read the rest of this entry »


Overview of Meta-Analysis, Part 2 (of 7): Sampling Error

In 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.)
Read the rest of this entry »