Many judgements are required in the process of preparing a meta-analysis. Prediction intervals from random-effects meta-analyses are a useful device for presenting the extent of between-study variation. Random-effects meta-analyses allow for heterogeneity by assuming that underlying effects follow a normal distribution, but they must be interpreted carefully. Variation across studies (heterogeneity) must be considered, although most Cochrane Reviews do not have enough studies to allow for the reliable investigation of its causes. For rare events, the Peto method has been observed to be less biased and more powerful than other methods. Studies with no events contribute no information about the risk ratio or odds ratio. Most meta-analysis methods are variations on a weighted average of the effect estimates from the different studies.
dichotomous, continuous) that result from measurement of an outcome in an individual study, and to choose suitable effect measures for comparing intervention groups. It is important to be familiar with the type of data (e.g. However, they also have the potential to mislead seriously, particularly if specific study designs, within-study biases, variation across studies, and reporting biases are not carefully considered. Potential advantages of meta-analyses include an improvement in precision, the ability to answer questions not posed by individual studies, and the opportunity to settle controversies arising from conflicting claims. Meta-analysis is the statistical combination of results from two or more separate studies.
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