dependent effect sizes

POMADE

Power for Meta-Analysis of Dependent Effects

Power approximations for overall average effects in meta-analysis of dependent effect sizes

Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based …

Investigating narrative performance in children with developmental language disorder: A systematic review and meta-analysis

__Purpose__: Speech-language pathologists (SLPs) typically examine narrative performance when completing a comprehensive language assessment. However, there is significant variability in the methodologies used to evaluate narration. The primary aims …

Meta-Analysis with robust variance estimation: Expanding the range of working models

In prevention science and related fields, large meta-analyses are common, and these analyses often involve dependent effect size estimates. Robust variance estimation (RVE) methods provide a way to include all dependent effect sizes in a single …

Variance component estimates in meta-analysis with mis-specified sampling correlation

\[ \def\Pr{{\text{Pr}}} \def\E{{\text{E}}} \def\Var{{\text{Var}}} \def\Cov{{\text{Cov}}} \] In a recent paper with Beth Tipton, we proposed new working models for meta-analyses involving dependent effect sizes. The central idea of our approach is to use a working model that captures the main features of the effect size data, such as by allowing for both between- and within-study heterogeneity in the true effect sizes (rather than only between-study heterogeneity).

Evaluating meta-analytic methods to detect selective reporting in the presence of dependent effect sizes

Meta-analysis is a set of statistical tools used to synthesize results from multiple studies evaluating a common research question. Two methodological challenges when conducting meta-analysis include selective reporting and correlated dependent …

What do meta-analysts mean by 'multivariate' meta-analysis?

If you’ve ever had class with me or attended one of my presentations, you’ve probably heard me grouse about how statisticians are mostly awful about naming things.1 A lot of the terminology in our field is pretty bad and ineloquent.

Sometimes, aggregating effect sizes is fine

In meta-analyses of psychology, education, and other social science research, it is very common that some of the included studies report more than one relevant effect size. For example, in a meta-analysis of intervention effects on reading outcomes, some studies may have used multiple measures of reading outcomes (each of which meets inclusion criteria), or may have measured outcomes at multiple follow-up times; some studies might have also investigated more than one version of an intervention, and it might be of interest to include effect sizes comparing each version to the no-intervention control condition; and it’s even possible that some studies may have all of these features, potentially contributing lots of effect size estimates.

wildmeta

Cluster-wild bootstrap for meta-regression