Individual Participant Data Meta-Analysis: Example with R

Aggregated Data Meta-Analysis and IPDMA Traditional meta-analyses use aggregated or summary level information from studies or reports (Cooper & Patall, 2009; Riley et al., 2010). Analysts conducting aggregated data meta-analysis would look up relevant literature and code summary statistics needed to calculate one or more effect sizes from each study and also code the corresponding moderator variables. And, then run meta-regression models to (1) summarize effect size estimates across studies, (2) characterize variability in effect sizes across studies, and (3) explain the variability in the effect sizes.

What Should I Use to Quantify Heterogeneity in Meta-Analysis?

Meta-analysis Scientific researchers tend to produce literature on the same topic either to replicate or extend prior studies or due to a lack of awareness of prior evidence (Hedges & Cooper, 2009). Results across studies tend to vary, even when researchers try to replicate studies, due to differences in sample characteristics, research designs, analytic strategies or sampling error (Hedges & Cooper, 2009). Meta-analysis is a set of statistical techniques for synthesizing results from multiple primary studies on a common topic.