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Meta-Analysis

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Updated January 26, 2014

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Definition: A meta-analysis is a type of study that uses statistical techniques to analyze the combined results of a series of studies with related hypotheses that have been previously published. A meta-analysis is a type of pooled analysis uses special statistical techniques to combine the results of other studies in ways that take into account the original study's design and quality. Another name for meta analysis is quantitative review, which distinguishes this type of study from typical review studies that look at the results of numerous studies without reanalyzing or combining their data.

Meta analysis is a useful tool in the scientist's arsenal, since it provides a quantitative, and somewhat objective, way to combine the results of various studies on the same topic. This allows scientists to try to analyze how the results of the studies, which may be very different, combine to form a more complete picture. Combining studies can also allow scientists to find out whether a small effect was significant, something that may be difficult to do in a single study that has fewer enrollees.

The biggest weakness of meta-analysis is that it relies only on pre-existing studies rather than any original data collection. This means that any flaws that consistently run through the early studies may be magnified in the meta-analysis. Meta analysis may also be hampered by publication bias -- if there is a tendency for journals to only publish positive results (and not studies that show little to no effect), then the magnitude of an association seen in a pooled analysis may seem to be larger than it actually is.

Also Known As: quantitative review, pooled analysis
Alternate Spellings: meta analysis
Examples:
A 2009 meta-analysis of six studies that peripherally addressed the use of condoms to prevent genital herpes transmission found that using condoms did seem to be an effective method to reduce the sexual transmission of HSV2.

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