Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 3 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 6 |
Descriptor
Source
| Research Synthesis Methods | 6 |
Author
| Christian Röver | 1 |
| Christoph Schürmann | 1 |
| Domínguez Islas, Clara | 1 |
| Jia, Yulong | 1 |
| Jona Lilienthal | 1 |
| Li, Ling | 1 |
| Matthias Maiworm | 1 |
| Meader, N. | 1 |
| Mengersen, K. | 1 |
| Ohmann, Christian | 1 |
| Okada, Kensuke | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 6 |
| Information Analyses | 4 |
| Reports - Research | 3 |
| Reports - Descriptive | 1 |
Education Level
Audience
Location
| Germany | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
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
Yao, Minghong; Wang, Yuning; Ren, Yan; Jia, Yulong; Zou, Kang; Li, Ling; Sun, Xin – Research Synthesis Methods, 2023
Rare events meta-analyses of randomized controlled trials (RCTs) are often underpowered because the outcomes are infrequent. Real-world evidence (RWE) from non-randomized studies may provide valuable complementary evidence about the effects of rare events, and there is growing interest in including such evidence in the decision-making process.…
Descriptors: Evidence, Meta Analysis, Randomized Controlled Trials, Decision Making
Okada, Kensuke – Research Synthesis Methods, 2015
This paper proposes a new method to evaluate informative hypotheses for meta-analysis of Cronbach's coefficient alpha using a Bayesian approach. The coefficient alpha is one of the most widely used reliability indices. In meta-analyses of reliability, researchers typically form specific informative hypotheses beforehand, such as "alpha of…
Descriptors: Correlation, Bayesian Statistics, Meta Analysis, Hypothesis Testing
Stewart, G. B.; Mengersen, K.; Meader, N. – Research Synthesis Methods, 2014
Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention.…
Descriptors: Bayesian Statistics, Networks, Cognitive Mapping, Data Collection
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

Peer reviewed
Direct link
