Focus on Data: Statistical Significance, Effect Size and the Accumulation of Evidence Achieved by Combining Study...

To provide information and perspectives on statistical significance and on meta-analysis, a statistical procedure for combining estimated effects across multiple studies.

Methods are presented for performing a meta-analysis in which results across multiple studies are combined. An example of a meta-analysis of optical coherence tomography thickness of the retina in patients with multiple sclerosis across multiple studies is provided. We show how to combine individual study results and how to weight the results of each study based on its reliability. The method of a meta-analysis is used to derive from all study results a pooled estimate that is closest to the unknown common effect.

Differences between the two most common methods for meta-analysis, the fixed-effects approach and the random-effects approach, are reviewed. Meta-analysis is applied to the study of the differences in the thickness of the retinal nerve fiber layers of healthy controls and patients with multiple sclerosis, showing why this is a useful procedure for combining estimated effects across multiple studies to derive the magnitude of retinal thinning caused by multiple sclerosis.

This review provides information and perspectives on statistical significance and on meta-analysis, a statistical procedure for combining estimated effects across multiple studies. A discussion is provided to show why statistical significance and low probability values are not all that matter and why investigators should also look at the magnitude of the estimated effects. Combining estimated effects across multiple studies with proper weighting of individual results is the goal of meta-analysis.