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Mathur, Maya B.; VanderWeele, Tyler J. – Research Synthesis Methods, 2021
Meta-regression analyses usually focus on estimating and testing differences in average effect sizes between individual levels of each meta-regression covariate in turn. These metrics are useful but have limitations: they consider each covariate individually, rather than in combination, and they characterize only the mean of a potentially…
Descriptors: Regression (Statistics), Meta Analysis, Effect Size, Computation
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Weber, Frank; Knapp, Guido; Glass, Änne; Kundt, Günther; Ickstadt, Katja – Research Synthesis Methods, 2021
There exists a variety of interval estimators for the overall treatment effect in a random-effects meta-analysis. A recent literature review summarizing existing methods suggested that in most situations, the Hartung-Knapp/Sidik-Jonkman (HKSJ) method was preferable. However, a quantitative comparison of those methods in a common simulation study…
Descriptors: Meta Analysis, Computation, Intervals, Statistical Analysis
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Held, Leonhard; Matthews, Robert; Ott, Manuela; Pawel, Samuel – Research Synthesis Methods, 2022
It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects…
Descriptors: Bayesian Statistics, Statistical Inference, Hypothesis Testing, Credibility
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Jackson, Dan – Research Synthesis Methods, 2013
Statistical inference is problematic in the common situation in meta-analysis where the random effects model is fitted to just a handful of studies. In particular, the asymptotic theory of maximum likelihood provides a poor approximation, and Bayesian methods are sensitive to the prior specification. Hence, less efficient, but easily computed and…
Descriptors: Computation, Statistical Analysis, Meta Analysis, Statistical Inference
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Verde, Pablo E.; Ohmann, Christian – Research Synthesis Methods, 2015
Researchers may have multiple motivations for combining disparate pieces of evidence in a meta-analysis, such as generalizing experimental results or increasing the power to detect an effect that a single study is not able to detect. However, while in meta-analysis, the main question may be simple, the structure of evidence available to answer it…
Descriptors: Randomized Controlled Trials, Bayesian Statistics, Comparative Analysis, Evidence