What is a defining feature of meta-analyses?

What is a defining feature of meta-analyses?

• A. Statistical pooling of data across studies
• B. Narrative summary of selected studies with no stats
• C. Experimental replication
• D. Primary data collection

Answer: (A)

The defining feature is statistical pooling of data across multiple studies to produce a single quantitative estimate of the overall effect. By combining effect sizes from each study and weighting them by their precision, meta-analyses convert diverse results into one summary figure, often accompanied by measures of heterogeneity and confidence intervals. This approach increases statistical power and helps clarify what the body of evidence suggests beyond what any single study shows. Narrative summaries without statistics describe individual studies without combining them, so they don’t provide the pooled estimate meta-analyses aim for. Experimental replication focuses on repeating a study’s methods to see if results hold, not on synthesizing existing results. Primary data collection involves gathering new data rather than merging existing findings.

The defining feature is statistical pooling of data across multiple studies to produce a single quantitative estimate of the overall effect. By combining effect sizes from each study and weighting them by their precision, meta-analyses convert diverse results into one summary figure, often accompanied by measures of heterogeneity and confidence intervals. This approach increases statistical power and helps clarify what the body of evidence suggests beyond what any single study shows.

Narrative summaries without statistics describe individual studies without combining them, so they don’t provide the pooled estimate meta-analyses aim for. Experimental replication focuses on repeating a study’s methods to see if results hold, not on synthesizing existing results. Primary data collection involves gathering new data rather than merging existing findings.