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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
Seide, Svenja E.; Jensen, Katrin; Kieser, Meinhard – Research Synthesis Methods, 2020
The performance of statistical methods is often evaluated by means of simulation studies. In case of network meta-analysis of binary data, however, simulations are not currently available for many practically relevant settings. We perform a simulation study for sparse networks of trials under between-trial heterogeneity and including multi-arm…
Descriptors: Bayesian Statistics, Meta Analysis, Data Analysis, Networks
Lin, Lifeng; Chu, Haitao – Research Synthesis Methods, 2018
In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of…
Descriptors: Bayesian Statistics, Multivariate Analysis, Meta Analysis, Correlation
Günhan, Burak Kürsad; Röver, Christian; Friede, Tim – Research Synthesis Methods, 2020
Meta-analyses of clinical trials targeting rare events face particular challenges when the data lack adequate numbers of events for all treatment arms. Especially when the number of studies is low, standard random-effects meta-analysis methods can lead to serious distortions because of such data sparsity. To overcome this, we suggest the use of…
Descriptors: Meta Analysis, Medical Research, Drug Therapy, Bayesian Statistics
Kim, Mi-Ok; Wang, Xia; Liu, Chunyan; Dorris, Kathleen; Fouladi, Maryam; Song, Seongho – Research Synthesis Methods, 2017
Phase I trials aim to establish appropriate clinical and statistical parameters to guide future clinical trials. With individual trials typically underpowered, systematic reviews and meta-analysis are desired to assess the totality of evidence. A high percentage of zero or missing outcomes often complicate such efforts. We use a systematic review…
Descriptors: Meta Analysis, Synthesis, Literature Reviews, Pediatrics
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

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