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Paschalis Karakasis; Konstantinos I. Bougioukas; Konstantinos Pamporis; Nikolaos Fragakis; Anna-Bettina Haidich – Research Synthesis Methods, 2024
This study aimed to assess the methods and outcomes of The Measurement Tool to Assess systematic Reviews (AMSTAR) 2 appraisals in overviews of reviews (overviews) of interventions in the cardiovascular field and identify factors that are associated with these outcomes. MEDLINE, Scopus, and the Cochrane Database of Systematic Reviews were searched…
Descriptors: Human Body, Intervention, Literature Reviews, Measurement Techniques
Lu Qin; Shishun Zhao; Wenlai Guo; Tiejun Tong; Ke Yang – Research Synthesis Methods, 2024
The application of network meta-analysis is becoming increasingly widespread, and for a successful implementation, it requires that the direct comparison result and the indirect comparison result should be consistent. Because of this, a proper detection of inconsistency is often a key issue in network meta-analysis as whether the results can be…
Descriptors: Meta Analysis, Network Analysis, Bayesian Statistics, Comparative Analysis
Guido Schwarzer; Gerta Rücker; Cristina Semaca – Research Synthesis Methods, 2024
The "LFK" index has been promoted as an improved method to detect bias in meta-analysis. Putatively, its performance does not depend on the number of studies in the meta-analysis. We conducted a simulation study, comparing the "LFK" index test to three standard tests for funnel plot asymmetry in settings with smaller or larger…
Descriptors: Bias, Meta Analysis, Simulation, Evaluation Methods
Yasushi Tsujimoto; Yusuke Tsutsumi; Yuki Kataoka; Akihiro Shiroshita; Orestis Efthimiou; Toshi A. Furukawa – Research Synthesis Methods, 2024
Meta-analyses examining dichotomous outcomes often include single-zero studies, where no events occur in intervention or control groups. These pose challenges, and several methods have been proposed to address them. A fixed continuity correction method has been shown to bias estimates, but it is frequently used because sometimes software (e.g.,…
Descriptors: Meta Analysis, Literature Reviews, Epidemiology, Error Correction
de Jong, Valentijn M. T.; Campbell, Harlan; Maxwell, Lauren; Jaenisch, Thomas; Gustafson, Paul; Debray, Thomas P. A. – Research Synthesis Methods, 2023
A common problem in the analysis of multiple data sources, including individual participant data meta-analysis (IPD-MA), is the misclassification of binary variables. Misclassification may lead to biased estimators of model parameters, even when the misclassification is entirely random. We aimed to develop statistical methods that facilitate…
Descriptors: Classification, Meta Analysis, Bayesian Statistics, Evaluation Methods
Weibel, Stephanie; Popp, Maria; Reis, Stefanie; Skoetz, Nicole; Garner, Paul; Sydenham, Emma – Research Synthesis Methods, 2023
Evidence synthesis findings depend on the assumption that the included studies follow good clinical practice and results are not fabricated or false. Studies which are problematic due to scientific misconduct, poor research practice, or honest error may distort evidence synthesis findings. Authors of evidence synthesis need transparent mechanisms…
Descriptors: Identification, Randomized Controlled Trials, Integrity, Evaluation Methods
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
van Aert, Robbie C. M. – Research Synthesis Methods, 2023
The partial correlation coefficient (PCC) is used to quantify the linear relationship between two variables while taking into account/controlling for other variables. Researchers frequently synthesize PCCs in a meta-analysis, but two of the assumptions of the common equal-effect and random-effects meta-analysis model are by definition violated.…
Descriptors: Correlation, Meta Analysis, Sampling, Simulation
Kylie E. Hunter; Mason Aberoumand; Sol Libesman; James X. Sotiropoulos; Jonathan G. Williams; Jannik Aagerup; Rui Wang; Ben W. Mol; Wentao Li; Angie Barba; Nipun Shrestha; Angela C. Webster; Anna Lene Seidler – Research Synthesis Methods, 2024
Increasing concerns about the trustworthiness of research have prompted calls to scrutinise studies' Individual Participant Data (IPD), but guidance on how to do this was lacking. To address this, we developed the IPD Integrity Tool to screen randomised controlled trials (RCTs) for integrity issues. Development of the tool involved a literature…
Descriptors: Integrity, Randomized Controlled Trials, Participant Characteristics, Computer Software
Bougioukas, Konstantinos I.; Diakonidis, Theodoros; Mavromanoli, Anna C.; Haidich, Anna-Bettina – Research Synthesis Methods, 2023
An overview of reviews aims to collect, assess, and synthesize evidence from multiple systematic reviews (SRs) on a specific topic using rigorous and reproducible methods. An important methodological challenge in conducting an overview of reviews is the management of overlapping data due to the inclusion of the same primary studies in SRs. We…
Descriptors: Programming Languages, Open Source Technology, Evaluation Methods, Evidence
Caspar J. Van Lissa; Eli-Boaz Clapper; Rebecca Kuiper – Research Synthesis Methods, 2024
The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and…
Descriptors: Hypothesis Testing, Evaluation Methods, Replication (Evaluation), Sample Size
Yu-Kang Tu; Pei-Chun Lai; Yen-Ta Huang; James Hodges – Research Synthesis Methods, 2024
Network meta-analysis (NMA) incorporates all available evidence into a general statistical framework for comparing multiple treatments. Standard NMAs make three major assumptions, namely homogeneity, similarity, and consistency, and violating these assumptions threatens an NMA's validity. In this article, we suggest a graphical approach to…
Descriptors: Visualization, Meta Analysis, Comparative Analysis, Statistical Studies
Konstantinos I. Bougioukas; Paschalis Karakasis; Konstantinos Pamporis; Emmanouil Bouras; Anna-Bettina Haidich – Research Synthesis Methods, 2024
Systematic reviews (SRs) have an important role in the healthcare decision-making practice. Assessing the overall confidence in the results of SRs using quality assessment tools, such as "A MeaSurement Tool to Assess Systematic Reviews 2" (AMSTAR 2), is crucial since not all SRs are conducted using the most rigorous methods. In this…
Descriptors: Programming Languages, Research Methodology, Decision Making, Medical Research
Li, Hua; Shih, Ming-Chieh; Tu, Yu-Kang – Research Synthesis Methods, 2023
Component network meta-analysis (CNMA) compares treatments comprising multiple components and estimates the effects of individual components. For network meta-analysis, a standard network plot with nodes for treatments and edges for direct comparisons between treatments is drawn to visualize the evidence structure and the connections between…
Descriptors: Networks, Meta Analysis, Graphs, Comparative Analysis
Yuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
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