Meta analysis

Meta-analysis is a statistical technique used in statistical analysis, epidemiology and social sciences that combines or integrates the results of multiple scientific studies. Meta-analysis can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived.

Overview[edit | edit source]

Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This approach has the potential to yield more precise estimates of effects and to resolve uncertainty when reports disagree. Meta-analysis has been used extensively in epidemiology and evidence-based medicine today, and in business and social science and education.

Methodology[edit | edit source]

The main steps of a meta-analysis are data collection, data extraction, statistical analysis, and interpretation. The statistical analysis combines the results of several studies that address a set of related research hypotheses. This is usually done by identification of a common measure of effect size, for which a weighted average might be the output of a meta-analysis.

Advantages and Disadvantages[edit | edit source]

The key advantage of meta-analysis is its capacity to increase power and precision and improve estimates of the size of the effect. It can also allow for the exploration of sources of disagreement among results from different studies. However, it also has its disadvantages such as its susceptibility to publication bias and the quality of the included studies.

Applications[edit | edit source]

Meta-analysis is widely used in various fields such as medicine, psychology, public policy, business, and education. In medicine, it is often used to assess the efficacy of a treatment or intervention.