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Jona Lilienthal; Sibylle Sturtz; Christoph Schürmann; Matthias Maiworm; Christian Röver; Tim Friede; Ralf Bender – Research Synthesis Methods, 2024
In Bayesian random-effects meta-analysis, the use of weakly informative prior distributions is of particular benefit in cases where only a few studies are included, a situation often encountered in health technology assessment (HTA). Suggestions for empirical prior distributions are available in the literature but it is unknown whether these are…
Descriptors: Bayesian Statistics, Meta Analysis, Health Sciences, Technology
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Domínguez Islas, Clara; Rice, Kenneth M. – Research Synthesis Methods, 2022
Bayesian methods seem a natural choice for combining sources of evidence in meta-analyses. However, in practice, their sensitivity to the choice of prior distribution is much less attractive, particularly for parameters describing heterogeneity. A recent non-Bayesian approach to fixed-effects meta-analysis provides novel ways to think about…
Descriptors: Bayesian Statistics, Evidence, Meta Analysis, Statistical Inference
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Kwon, Deukwoo; Reddy, Roopesh Reddy Sadashiva; Reis, Isildinha M. – Research Synthesis Methods, 2021
In meta-analysis based on continuous outcome, estimated means and corresponding standard deviations from the selected studies are key inputs to obtain a pooled estimate of the mean and its confidence interval. We often encounter the situation that these quantities are not directly reported in the literatures. Instead, other summary statistics are…
Descriptors: Meta Analysis, Computation, Bayesian Statistics, Computer Oriented Programs