Sneak Preview 2: Outliers, Metric Transformation, and ES Distribution
Posted: May 31, 2012 | Author: A. R. Hafdahl | Filed under: Sneak Preview | Tags: assumption violation, between-studies variance component, conditional variance, correlation, effect size, fixed effect, heterogeneity, interval estimation, meta-analysis, outlier, random effect, substantive application | Leave a commentMy previous three posts on fitting models to effect sizes (ESs)—Parts 5a, 5b, and 5c—were the core of my seven-part overview of meta-analysis. With only two posts remaining in the overview, I’ll pause again to describe three more methodological issues I plan to discuss: potential outliers, transforming ES metrics, and the distribution of ES parameters. As in my first sneak preview—about degraded ESs and tricky conditional variances (CVs)—I’ll keep these “teaser” descriptions fairly short, mainly to pique your interest; each issue deserves at least one dedicated post with more detail.
Read the rest of this entry »
Sneak Preview: Degraded Effect Sizes and Tricky Conditional Variances
Posted: April 2, 2012 | Author: A. R. Hafdahl | Filed under: Sneak Preview | Tags: Bayesian analysis, conditional variance, correlation, effect size, meta-analysis, missing data, resampling, significance testing, standardized mean difference, vote counting | Leave a commentMy post on data exploration more than half completed my seven-part overview of meta-analysis. As a diversion while I write Part 5, let’s consider two of several methodological issues I plan to discuss in this blog: degraded effect sizes (ESs) and tricky conditional variances (CVs). My main aim here is to pique your interest in future posts by offering a glimpse at ways to manage selected challenges that routine meta-analytic techniques don’t address. These “teaser” descriptions will be quite superficial. I plan to elaborate on each of these challenges—as well as many others—after laying a foundation in my seven-part overview.
Read the rest of this entry »
Meta-Analysis Sandwich 