Common Errors in Statistics (and How to Avoid Them), 4th Edition

META-ANALYSIS

Meta-analysis is a set of techniques that allow us to combine the results of a series of small trials and observational studies. With the appropriate meta-analysis, we can, in theory, obtain more precise estimates of main effects, test a priori hypotheses about subgroups, and determine the number of observations needed for large-scale randomized trials.

By putting together all available data, meta-analyses are also better placed than individual trials to answer questions about whether an overall study result varies among subgroups—for example, among men and women, older and younger patients, or subjects with different degrees of severity of disease.

Meta-analysis should be viewed as an observational study of the evidence. The steps involved are similar to any other research undertaking: formulation of the problem to be addressed, collection and analysis of the data, and reporting of the results. Researchers should write in advance a detailed research protocol that clearly states the objectives, the hypotheses to be tested, the subgroups of interest, and the proposed methods and criteria for identifying and selecting relevant studies and extracting and analysing information.

—Egger, Smith, and Phillips [1997]³⁴

Too many studies end with inconclusive results because of the relatively small number of observations that were made. The researcher can not quite reject the null hypothesis, but is not quite ready to embrace the null hypothesis, either. As we saw in Chapter ...