Journal ArticleDOI
Fixed- and random-effects models in meta-analysis.
Larry V. Hedges,Jack L. Vevea +1 more
TLDR
In this paper, the authors evaluate the performance of confidence intervals and hypothesis tests when each type of statistical procedure is used for each kind of inference and confirm that each procedure is best for making the kind of inferences for which it was designed.Abstract:
There are 2 families of statistical procedures in meta-analysis: fixed- and randomeffects procedures. They were developed for somewhat different inference goals: making inferences about the effect parameters in the studies that have been observed versus making inferences about the distribution of effect parameters in a population of studies from a random sample of studies. The authors evaluate the performance of confidence intervals and hypothesis tests when each type of statistical procedure is used for each type of inference and confirm that each procedure is best for making the kind of inference for which it was designed. Conditionally random-effects procedures (a hybrid type) are shown to have properties in between those of fixed- and random-effects procedures. The use of quantitative methods to summarize the results of several empirical research studies, or metaanalysis, is now widely used in psychology, medicine, and the social sciences. Meta-analysis usually involves describing the results of each study by means of a numerical index (an estimate of effect size, such as a correlation coefficient, a standardized mean difference, or an odds ratio) and then combining these estimates across studies to obtain a summary. Two somewhat different statistical models have been developed for inference about average effect size from a collection of studies, called the fixed-effects and random-effects models. (A third alternative, the mixedeffects model, arises in conjunction with analyses involving study-level covariates or moderator variables, which we do not consider in this article; see Hedges, 1992.) Fixed-effects models treat the effect-size parameters as fixed but unknown constants to be estimated and usually (but not necessarily) are used in conjunction with assumptions about the homogeneity of effect parameters (see, e.g., Hedges, 1982; Rosenthal & Rubin, 1982). Random-effects models treat the effectsize parameters as if they were a random sample fromread more
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Book
Cochrane Handbook for Systematic Reviews of Interventions
Julian P T Higgins,Sally Green +1 more
TL;DR: The Cochrane Handbook for Systematic Reviews of Interventions is the official document that describes in detail the process of preparing and maintaining Cochrane systematic reviews on the effects of healthcare interventions.
Journal ArticleDOI
Meta-Analysis: A Constantly Evolving Research Integration Tool
TL;DR: The four articles in this special section onMeta-analysis illustrate some of the complexities entailed in meta-analysis methods and contributes both to advancing this methodology and to the increasing complexities that can befuddle researchers.
Journal ArticleDOI
Conducting Meta-Analyses in R with the metafor Package
TL;DR: The metafor package provides functions for conducting meta-analyses in R and includes functions for fitting the meta-analytic fixed- and random-effects models and allows for the inclusion of moderators variables (study-level covariates) in these models.
Journal ArticleDOI
Social Relationships and Mortality Risk: A Meta-analytic Review
TL;DR: In a meta-analysis, Julianne Holt-Lunstad and colleagues find that individuals' social relationships have as much influence on mortality risk as other well-established risk factors for mortality, such as smoking.
Journal ArticleDOI
Emotion-regulation strategies across psychopathology: A meta-analytic review.
TL;DR: A large effect size is found for rumination, medium to large for avoidance, problem solving, and suppression, and small to medium for reappraisal and acceptance in the relationship between each regulatory strategy and each of the four psychopathology groups.
References
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Journal ArticleDOI
Meta-Analysis in Clinical Trials*
TL;DR: This paper examines eight published reviews each reporting results from several related trials in order to evaluate the efficacy of a certain treatment for a specified medical condition and suggests a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.
Book
Statistical Methods for Meta-Analysis
Larry V. Hedges,Ingram Olkin +1 more
TL;DR: In this article, the authors present a model for estimating the effect size from a series of experiments using a fixed effect model and a general linear model, and combine these two models to estimate the effect magnitude.
Journal ArticleDOI
Statistical Methods for Meta-Analysis.
TL;DR: In this paper, the authors present a model for estimating the effect size from a series of experiments using a fixed effect model and a general linear model, and combine these two models to estimate the effect magnitude.
Book
Methods of Meta-Analysis: Correcting Error and Bias in Research Findings
John E. Hunter,Frank L. Schmidt +1 more
TL;DR: In this article, the authors present a meta-analysis of Artifact Distributions and their impact on study outcomes. But they focus mainly on the second-order sampling error and related issues.
Journal ArticleDOI
Distribution Theory for Glass's Estimator of Effect size and Related Estimators:
TL;DR: In this article, the effect size estimator of Glass's estimator, the sample mean difference divided by the sample standard deviation, is studied in the context of an explicit statistical model.