---
title: "Meta-analysis"
chunk: 1/7
source: "https://en.wikipedia.org/wiki/Meta-analysis"
category: "reference"
tags: "science, encyclopedia"
date_saved: "2026-05-05T04:26:08.077779+00:00"
instance: "kb-cron"
---

Meta-analysis is a method of synthesis of quantitative data from multiple independent studies addressing a common research question. An important part of this method involves computing a combined effect size across all of the studies. As such, this statistical approach involves extracting effect sizes and variance measures from various studies. By combining these effect sizes the statistical power is improved and can resolve uncertainties or discrepancies found in individual studies. Meta-analyses are integral in supporting research grant proposals, shaping treatment guidelines, and influencing health policies. They are also pivotal in summarizing existing research to guide future studies, thereby cementing their role as a fundamental methodology in metascience. Meta-analyses are often, but not always, important components of a systematic review.

== History ==
The term "meta-analysis" was coined in 1976 by the statistician Gene Glass, who stated "Meta-analysis refers to the analysis of analyses". Glass's work aimed at describing aggregated measures of relationships and effects. While Glass is credited with authoring the first modern meta-analysis, a paper published in 1904 by the statistician Karl Pearson in the British Medical Journal collated data from several studies of typhoid inoculation and is seen as the first time a meta-analytic approach was used to aggregate the outcomes of multiple clinical studies. Numerous other examples of early meta-analyses can be found including occupational aptitude testing, and agriculture.
The first model meta-analysis was published in 1978 on the effectiveness of psychotherapy outcomes by Mary Lee Smith and Gene Glass. After publication of their article there was pushback on the usefulness and validity of meta-analysis as a tool for evidence synthesis. The first example of this was by Hans Eysenck who in a 1978 article in response to the work done by Mary Lee Smith and Gene Glass called meta-analysis an "exercise in mega-silliness". Later Eysenck would refer to meta-analysis as "statistical alchemy". Despite these criticisms the use of meta-analysis has only grown since its modern introduction. By 1991 there were 334 published meta-analyses; this number grew to 9,135 by 2014.
The field of meta-analysis expanded greatly since the 1970s and touches multiple disciplines including psychology, medicine, and ecology. Further the more recent creation of evidence synthesis communities has increased the cross pollination of ideas, methods, and the creation of software tools across disciplines.

== Literature search ==
One of the most important steps of a meta-analysis is data collection. For an efficient database search, appropriate keywords and search limits need to be identified. The use of Boolean operators and search limits can assist the literature search. A number of databases are available (e.g., PubMed, Embase, PsychInfo), however, it is up to the researcher to choose the most appropriate sources for their research area. Indeed, many scientists use duplicate search terms within two or more databases to cover multiple sources. The reference lists of eligible studies can also be searched for eligible studies (i.e., snowballing). The initial search may return a large volume of studies. Quite often, the abstract or the title of the manuscript reveals that the study is not eligible for inclusion, based on the pre-specified criteria. These studies can be discarded. However, if it appears that the study may be eligible (or even if there is some doubt) the full paper can be retained for closer inspection. The references lists of eligible articles can also be searched for any relevant articles. These search results need to be detailed in a PRIMSA flow diagram which details the flow of information through all stages of the review. Thus, it is important to note how many studies were returned after using the specified search terms and how many of these studies were discarded, and for what reason. The search terms and strategy should be specific enough for a reader to reproduce the search. The date range of studies, along with the date (or date period) the search was conducted should also be provided.
A data collection form provides a standardized means of collecting data from eligible studies. For a meta-analysis of correlational data, effect size information is usually collected as Pearson's r statistic. Partial correlations are often reported in research, however, these may inflate relationships in comparison to zero-order correlations. Moreover, the partialed out variables will likely vary from study-to-study. As a consequence, many meta-analyses exclude partial correlations from their analysis. As a final resort, plot digitizers can be used to scrape data points from scatterplots (if available) for the calculation of Pearson's r. Data reporting important study characteristics that may moderate effects, such as the mean age of participants, should also be collected. A measure of study quality can also be included in these forms to assess the quality of evidence from each study. There are more than 80 tools available to assess the quality and risk of bias in observational studies reflecting the diversity of research approaches between fields. These tools usually include an assessment of how dependent variables were measured, appropriate selection of participants, and appropriate control for confounding factors. Other quality measures that may be more relevant for correlational studies include sample size, psychometric properties, and reporting of methods.
A final consideration is whether to include studies from the gray literature, which is defined as research that has not been formally published. This type of literature includes conference abstracts, dissertations, and pre-prints. While the inclusion of gray literature reduces the risk of publication bias, the methodological quality of the work is often (but not always) lower than formally published work. Reports from conference proceedings, which are the most common source of gray literature, are poorly reported and data in the subsequent publication is often inconsistent, with differences observed in almost 20% of published studies.

== Methods and assumptions ==