Basic aspects of meta-analysis. Part 1

Abstract

Meta-analysis is one of the concepts of scientific methodology, and is a frequent but optional component of systematic reviews of empirical research. It joins the results of several scientific studies and tests one or more interrelated scientific hypotheses using quantitative (statistical) methods. This analysis can either use primary data from the original studies or published (secondary) results of studies dealing with the same problem. Meta-analysis is used to obtain an estimate of the magnitude of an unknown effect, and compare the results of different studies, identifying patterns or other relationships in them, as well as possible sources of disagreement. Meta-analyses are the highest level of credibility within evidence-based medicine (EBM), so meta-analysis results are considered as the most reliable source of evidence. Understanding all the procedures of a meta-analysis will allow researchers to analyze the results of such studies correctly, as well as formulate tasks when conducting meta-analyses on their own. In this article the reader will be introduced to key concepts such as weighted effects, heterogeneity, the different types of statistical models used, and how to work with some of the types of plots produced in meta-analyses.