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Meta-analysis is the statistical procedure for combining data from multiple studies. When the treatment effect(or effect size) is consistent from one study to the next, meta-analysis can be used to identify this common effect. When the effect varies from one study to the next, meta-analysis may be used to identify the reason for the variation.
Decisions about the utility of an intervention or the validity of a hypothesis cannot be based on the results of a single study, because results typically vary from one study to the next. Rather, a mechanism is needed to synthesize data across studies. Narrative reviews had been used for this purpose, but the narrative review is largely subjective (different experts can come to different conclusions) and becomes impossibly difficult when there are more than a few studies involved. Meta-analysis, by contrast, applies objective formulas (much as one would apply statistics to data within a single study), and can be used with any number of studies.
Pharmaceutical companies use meta-analysis to gain approval for new drugs, with regulatory agencies sometimes requiring a meta-analysis as part of the approval process. Clinicians and applied researchers in medicine, education, psychology, criminal justice, and a host of other fields use meta-analysis to determine which interventions work, and which ones work best. Meta analysis is also widely used in basic research to evaluate the evidence in areas as diverse as sociology, social psychology, sex differences, finance and economics, political science, marketing, ecology and genetics, among others.