Publication Date
In 2025 | 0 |
Since 2024 | 11 |
Descriptor
Comparative Analysis | 11 |
Meta Analysis | 4 |
Computer Software | 3 |
Evaluation Methods | 3 |
Medical Research | 3 |
Outcomes of Treatment | 3 |
Research Reports | 3 |
Simulation | 3 |
Artificial Intelligence | 2 |
Decision Making | 2 |
Evaluators | 2 |
More ▼ |
Source
Research Synthesis Methods | 11 |
Author
Dan Jackson | 2 |
Landan Zhang | 2 |
Andrew Forbes | 1 |
Azza Warraitch | 1 |
Benoît Rihoux | 1 |
Chang Xu | 1 |
Chris Doucouliagos | 1 |
Cynthia M. Kroeger | 1 |
Elizabeth Korevaar | 1 |
Haitao Chu | 1 |
James Hodges | 1 |
More ▼ |
Publication Type
Journal Articles | 11 |
Reports - Research | 6 |
Reports - Evaluative | 5 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Landan Zhang; Sylwia Bujkiewicz; Dan Jackson – Research Synthesis Methods, 2024
Simulated treatment comparison (STC) is an established method for performing population adjustment for the indirect comparison of two treatments, where individual patient data (IPD) are available for one trial but only aggregate level information is available for the other. The most commonly used method is what we call 'standard STC'. Here we fit…
Descriptors: Simulation, Patients, Outcomes of Treatment, Comparative Analysis
Landan Zhang; Dan Jackson – Research Synthesis Methods, 2024
A recent paper proposed an alternative weighting scheme when performing matching-adjusted indirect comparisons. This alternative approach follows the conventional one in matching the covariate means across two studies but differs in that it maximizes the effective sample size when doing so. The appendix of this paper showed, assuming there is one…
Descriptors: Comparative Analysis, Medical Research, Sample Size, Research Methodology
Stephan B. Bruns; Teshome K. Deressa; T. D. Stanley; Chris Doucouliagos; John P. A. Ioannidis – Research Synthesis Methods, 2024
Using a sample of 70,399 published p-values from 192 meta-analyses, we empirically estimate the counterfactual distribution of p-values in the absence of any biases. Comparing observed p-values with counterfactually expected p-values allows us to estimate how many p-values are published as being statistically significant when they should have been…
Descriptors: Meta Analysis, Research Reports, Research Design, Microeconomics
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
Raju Kanukula; Joanne E. McKenzie; Lisa Bero; Zhaoli Dai; Sally McDonald; Cynthia M. Kroeger; Elizabeth Korevaar; Andrew Forbes; Matthew J. Page – Research Synthesis Methods, 2024
We aimed to explore, in a sample of systematic reviews (SRs) with meta-analyses of the association between food/diet and health-related outcomes, whether systematic reviewers selectively included study effect estimates in meta-analyses when multiple effect estimates were available. We randomly selected SRs of food/diet and health-related outcomes…
Descriptors: Meta Analysis, Intervention, Comparative Analysis, Food
Ziren Jiang; Joseph C. Cappelleri; Margaret Gamalo; Yong Chen; Neal Thomas; Haitao Chu – Research Synthesis Methods, 2024
Population-adjusted indirect comparison (PAIC) is an increasingly used technique for estimating the comparative effectiveness of different treatments for the health technology assessments when head-to-head trials are unavailable. Three commonly used PAIC methods include matching-adjusted indirect comparison (MAIC), simulated treatment comparison…
Descriptors: Comparative Analysis, Decision Making, Health Services, Computer Oriented Programs
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
Shijie Ren; Sa Ren; Nicky J. Welton; Mark Strong – Research Synthesis Methods, 2024
Population-adjusted indirect comparisons, developed in the 2010s, enable comparisons between two treatments in different studies by balancing patient characteristics in the case where individual patient-level data (IPD) are available for only one study. Health technology assessment (HTA) bodies increasingly rely on these methods to inform funding…
Descriptors: Medical Research, Outcomes of Treatment, Standards, Safety
Reem El Sherif; Pierre Pluye; Quan Nha Hong; Benoît Rihoux – Research Synthesis Methods, 2024
Qualitative comparative analysis (QCA) is a hybrid method designed to bridge the gap between qualitative and quantitative research in a case-sensitive approach that considers each case holistically as a complex configuration of conditions and outcomes. QCA allows for multiple conjunctural causation, implying that it is often a combination of…
Descriptors: Comparative Analysis, Qualitative Research, Statistical Analysis, Researchers
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
Qusai Khraisha; Sophie Put; Johanna Kappenberg; Azza Warraitch; Kristin Hadfield – Research Synthesis Methods, 2024
Systematic reviews are vital for guiding practice, research and policy, although they are often slow and labour-intensive. Large language models (LLMs) could speed up and automate systematic reviews, but their performance in such tasks has yet to be comprehensively evaluated against humans, and no study has tested Generative Pre-Trained…
Descriptors: Peer Evaluation, Research Reports, Artificial Intelligence, Computer Software