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Showing 1 to 15 of 483 results Save | Export
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Peter J. Godolphin; Nadine Marlin; Chantelle Cornett; David J. Fisher; Jayne F. Tierney; Ian R. White; Ewelina Rogozinska – Research Synthesis Methods, 2024
Individual participant data (IPD) meta-analyses of randomised trials are considered a reliable way to assess participant-level treatment effect modifiers but may not make the best use of the available data. Traditionally, effect modifiers are explored one covariate at a time, which gives rise to the possibility that evidence of treatment-covariate…
Descriptors: Meta Analysis, Randomized Controlled Trials, Statistical Analysis, Participant Characteristics
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Maya B. Mathur – Research Synthesis Methods, 2024
Meta-analyses can be compromised by studies' internal biases (e.g., confounding in nonrandomized studies) as well as publication bias. These biases often operate nonadditively: publication bias that favors significant, positive results selects indirectly for studies with more internal bias. We propose sensitivity analyses that address two…
Descriptors: Meta Analysis, Attribution Theory, Publications, Bias
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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
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Rrita Zejnullahi; Larry V. Hedges – Research Synthesis Methods, 2024
Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods…
Descriptors: Robustness (Statistics), Meta Analysis, Sample Size, Computation
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Timo Gnambs; Ulrich Schroeders – Research Synthesis Methods, 2024
Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing…
Descriptors: Accuracy, Meta Analysis, Randomized Controlled Trials, Effect Size
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Michelle M. Haby; Jorge Otávio Maia Barreto; Jenny Yeon Hee Kim; Sasha Peiris; Cristián Mansilla; Marcela Torres; Diego Emmanuel Guerrero-Magaña; Ludovic Reveiz – Research Synthesis Methods, 2024
Rapid review methodology aims to facilitate faster conduct of systematic reviews to meet the needs of the decision-maker, while also maintaining quality and credibility. This systematic review aimed to determine the impact of different methodological shortcuts for undertaking rapid reviews on the risk of bias (RoB) of the results of the review.…
Descriptors: Decision Making, Medical Research, Research Reports, Search Strategies
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Kollin W. Rott; Gert Bronfort; Haitao Chu; Jared D. Huling; Brent Leininger; Mohammad Hassan Murad; Zhen Wang; James S. Hodges – Research Synthesis Methods, 2024
Meta-analysis is commonly used to combine results from multiple clinical trials, but traditional meta-analysis methods do not refer explicitly to a population of individuals to whom the results apply and it is not clear how to use their results to assess a treatment's effect for a population of interest. We describe recently-introduced causally…
Descriptors: Meta Analysis, Causal Models, Outcomes of Treatment, Medical Research
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Andreas Halman; Alicia Oshlack – Research Synthesis Methods, 2024
A systematic review is a type of literature review that aims to collect and analyse all available evidence from the literature on a particular topic. The process of screening and identifying eligible articles from the vast amounts of literature is a time-consuming task. Specialised software has been developed to aid in the screening process and…
Descriptors: Literature Reviews, Medical Research, Computer Software, Users (Information)
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Céline Chapelle; Gwénaël Le Teuff; Paul Jacques Zufferey; Silvy Laporte; Edouard Ollier – Research Synthesis Methods, 2024
The number of meta-analyses of aggregate data has dramatically increased due to the facility of obtaining data from publications and the development of free, easy-to-use, and specialised statistical software. Even when meta-analyses include the same studies, their results may vary owing to different methodological choices. Assessment of the…
Descriptors: Meta Analysis, Replication (Evaluation), Data Analysis, Statistical Analysis
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Shifeng Liu; Florence T. Bourgeois; Claire Narang; Adam G. Dunn – Research Synthesis Methods, 2024
Searching for trials is a key task in systematic reviews and a focus of automation. Previous approaches required knowing examples of relevant trials in advance, and most methods are focused on published trial articles. To complement existing tools, we compared methods for finding relevant trial registrations given a International Prospective…
Descriptors: Artificial Intelligence, Medical Research, Experimental Groups, Control Groups
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Lauren Maxwell; Priya Shreedhar; Mabel Carabali; Brooke Levis – Research Synthesis Methods, 2024
Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognostic model development and evaluation. However,…
Descriptors: Research Methodology, Authors, Guides, Budgets
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Brinley N. Zabriskie; Nolan Cole; Jacob Baldauf; Craig Decker – Research Synthesis Methods, 2024
Meta-analyses have become the gold standard for synthesizing evidence from multiple clinical trials, and they are especially useful when outcomes are rare or adverse since individual trials often lack sufficient power to detect a treatment effect. However, when zero events are observed in one or both treatment arms in a trial, commonly used…
Descriptors: Meta Analysis, Error Correction, Computation, Simulation
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Andres Jung; Tobias Braun; Susan Armijo-Olivo; Dimitris Challoumas; Kerstin Luedtke – Research Synthesis Methods, 2024
External validity is an important parameter that needs to be considered for decision making in health research, but no widely accepted measurement tool for the assessment of external validity of randomized controlled trials (RCTs) exists. One of the most limiting factors for creating such a tool is probably the substantial heterogeneity and lack…
Descriptors: Randomized Controlled Trials, Validity, Delphi Technique, Definitions
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Lena Schmidt; Saleh Mohamed; Nick Meader; Jaume Bacardit; Dawn Craig – Research Synthesis Methods, 2024
The amount of grey literature and 'softer' intelligence from social media or websites is vast. Given the long lead-times of producing high-quality peer-reviewed health information, this is causing a demand for new ways to provide prompt input for secondary research. To our knowledge, this is the first review of automated data extraction methods or…
Descriptors: Automation, Natural Language Processing, Literature Reviews, Data Collection
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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
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