Meta-analysis

meta-analysesmeta analysismeta-analyticmetastudynetwork meta-analysismetaanalysisMeta-studiesmeta-studymeta studymeta-analysies
A meta-analysis is a statistical analysis that combines the results of multiple scientific studies.wikipedia
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Evidence-based medicine

evidence-basedmedical evidenceevidence
Although meta-analysis is widely used in epidemiology and evidence-based medicine today, a meta-analysis of a medical treatment was not published until 1955.
Although all medicine based on science has some degree of empirical support, EBM goes further, classifying evidence by its epistemologic strength and requiring that only the strongest types (coming from meta-analyses, systematic reviews, and randomized controlled trials) can yield strong recommendations; weaker types (such as from case-control studies) can yield only weak recommendations.

Frank L. Schmidt

In the 1970s, more sophisticated analytical techniques were introduced in educational research, starting with the work of Gene V. Glass, Frank L. Schmidt and John E. Hunter. The statistical theory surrounding meta-analysis was greatly advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt, and Douglas G. Bonett.
Schmidt also developed psychometric meta-analysis methods used in a wide variety of research areas.

Systematic review

systematic reviewsreviewsystematic literature review
Meta-analyses are often, but not always, important components of a systematic review procedure.
Systematic reviews often, but not always, use statistical techniques (meta-analysis) to combine results of eligible studies, or at least use scoring of the levels of evidence depending on the methodology used.

Gene V. Glass

Gene V GlassGene GlassGlass, Gene V.
In the 1970s, more sophisticated analytical techniques were introduced in educational research, starting with the work of Gene V. Glass, Frank L. Schmidt and John E. Hunter.
According to the science writer Morton Hunt, he coined the term "meta-analysis" and illustrated its first use in his presidential address to the American Educational Research Association in San Francisco in April, 1976.

Secondary source

secondary sourcessecondarysecondary literature
A meta-analysis is a secondary source.
In general, secondary sources are self-described as review articles or meta-analysis.

Larry V. Hedges

Larry HedgesHedges, Larry V.
The statistical theory surrounding meta-analysis was greatly advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt, and Douglas G. Bonett.
Larry Vernon Hedges is a researcher in statistical methods for meta-analysis and evaluation of education policy.

Ingram Olkin

Olkin, IngramI. Olkin
The statistical theory surrounding meta-analysis was greatly advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt, and Douglas G. Bonett.
He is known for developing statistical analysis for evaluating policies, particularly in education, and for his contributions to meta-analysis, statistics education, multivariate analysis, and majorization theory.

Nambury S. Raju

The statistical theory surrounding meta-analysis was greatly advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt, and Douglas G. Bonett.
Nambury S. Raju (1937 – October 27, 2005) was an American psychology professor known for his work in psychometrics, meta-analysis, and utility theory.

Cochrane (organisation)

Cochrane reviewCochrane CollaborationCochrane
Here it is convenient to follow the terminology used by the Cochrane Collaboration, and use "meta-analysis" to refer to statistical methods of combining evidence, leaving other aspects of 'research synthesis' or 'evidence synthesis', such as combining information from qualitative studies, for the more general context of systematic reviews.
The Cochrane logo represents a meta-analysis of data from seven randomised controlled trials (RCTs), comparing one health care treatment with a placebo in a blobbogram or forest plot.

Thomas C. Chalmers

The statistical theory surrounding meta-analysis was greatly advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt, and Douglas G. Bonett.
December 8, 1917, New York City – d. December 27, 1995, Lebanon, New Hampshire) was famous for his role in the development of the randomized controlled trial and meta-analysis in medical research.

Effect size

Cohen's deffect sizesmagnitude
The average effect size across all studies is computed as a weighted mean, whereby the weights are equal to the inverse variance of each study's effect estimator.
Effect sizes complement statistical hypothesis testing, and play an important role in power analyses, sample size planning, and in meta-analyses.

Research synthesis

Here it is convenient to follow the terminology used by the Cochrane Collaboration, and use "meta-analysis" to refer to statistical methods of combining evidence, leaving other aspects of 'research synthesis' or 'evidence synthesis', such as combining information from qualitative studies, for the more general context of systematic reviews.
Meta-analysis is the preferred technique of quantitative research synthesis in many fields, such as medical science.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PRISMAThe PRISMA statement
For reporting guidelines, see the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is an evidence-based minimum set of items aimed at helping authors to report a wide array of systematic reviews and meta-analyses that assess the benefits and harms of a health care intervention.

Jacob Cohen (statistician)

Jacob CohenCohen, JacobCohen
The statistical theory surrounding meta-analysis was greatly advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt, and Douglas G. Bonett.
Jacob Cohen (April 20, 1923 – January 20, 1998) was an American psychologist and statistician best known for his work on statistical power and effect size, which helped to lay foundations for current statistical meta-analysis and the methods of estimation statistics.

Meta-regression

Meta-regression is a tool used in meta-analysis to examine the impact of moderator variables on study effect size using regression-based techniques.

John E. Hunter

In the 1970s, more sophisticated analytical techniques were introduced in educational research, starting with the work of Gene V. Glass, Frank L. Schmidt and John E. Hunter. The statistical theory surrounding meta-analysis was greatly advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C. Chalmers, Robert Rosenthal, Frank L. Schmidt, and Douglas G. Bonett.
He co-authored two books and authored or co-authored over 200 articles and book chapters on a wide variety of methodological topics, including confirmatory and exploratory factor analysis, meta-analysis, measurement theory and methods, statistics, and research methods.

Joseph Banks Rhine

J. B. RhineJ.B. RhineJoseph B. Rhine
The first meta-analysis of all conceptually identical experiments concerning a particular research issue, and conducted by independent researchers, has been identified as the 1940 book-length publication Extrasensory Perception After Sixty Years, authored by Duke University psychologists J. G. Pratt, J. B. Rhine, and associates.
It has been recognized as the first meta-analysis in the history of science.

Individual participant data

In general, two types of evidence can be distinguished when performing a meta-analysis: individual participant data (IPD), and aggregate data (AD).
Individual participant data (also known as individual patient data, often abbreviated IPD) is raw data from individual participants, and is often used in the context of meta-analysis.

Educational research

education researcheducational researcherSciences of Education
In the 1970s, more sophisticated analytical techniques were introduced in educational research, starting with the work of Gene V. Glass, Frank L. Schmidt and John E. Hunter.

Joaquim Radua

Joaquim Radua is a Spanish psychiatrist and developer of methods for meta-analysis of neuroimaging studies.

Funnel plot

The distribution of effect sizes can be visualized with a funnel plot which (in its most common version) is a scatter plot of standard error versus the effect size.
A funnel plot is a graph designed to check for the existence of publication bias; funnel plots are commonly used in systematic reviews and meta-analyses.

Study heterogeneity

heterogeneitysystematic heterogeneity
The meta-analysis estimate represents a weighted average across studies and when there is heterogeneity this may result in the summary estimate not being representative of individual studies.
In statistics, study heterogeneity is a problem that can arise when attempting to undertake a meta-analysis.

Homogeneity (statistics)

homogeneityhomogeneousheterogeneity
In meta-analysis, which combines the data from several studies, homogeneity measures the differences or similarities between the several studies (see also Study heterogeneity).

Publication bias

File drawer problemfile drawer effectself-selecting nature of the positive reports
However, in performing a meta-analysis, an investigator must make choices which can affect the results, including deciding how to search for studies, selecting studies based on a set of objective criteria, dealing with incomplete data, analyzing the data, and accounting for or choosing not to account for publication bias.
The presence of publication bias was investigated in meta-analyses.

Forest plot

blobbogramblobbogram or forest plot
The results of a meta-analysis are often shown in a forest plot.
It was developed for use in medical research as a means of graphically representing a meta-analysis of the results of randomized controlled trials.