Meta-analysis - Pitfalls


A meta-analysis of several small studies does not predict the results of a single large study, especially in a field like medicine where results are truly unpredictable. Some have argued that a weakness of the method is that sources of bias are not controlled by the method. A good meta-analysis of badly designed studies will still result in bad statistics, according to Robert Slavin. Slavin has argued that only methodologically sound studies should be included in a meta-analysis, a practice he calls 'best evidence synthesis'. Other meta-analysts would include weaker studies, and add a study-level predictor variable that reflects the methodological quality of the studies to examine the effect of study quality on the effect size. However, Glass and colleagues argued that the better approach preserves variance in the study sample, casting as wide a net as possible, and that methodological selection criteria introduce unwanted subjectivity, defeating the purpose of the approach.

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