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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
Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Ian Thomas; Shannon Kugley; Karen Crotty; Meera Viswanathan; Barbara Nussbaumer-Streit; Graham Booth; Nathaniel Erskine; Amanda Konet; Robert Chew – Research Synthesis Methods, 2024
Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…
Descriptors: Data Collection, Evidence, Synthesis, Language Processing
Yu, Tianqi; Lin, Lifeng; Furuya-Kanamori, Luis; Xu, Chang – Research Synthesis Methods, 2022
In evidence-based practice, new topics generally only have a few studies available for synthesis. As a result, the evidence of such meta-analyses raised substantial concerns. We investigated the robustness of the evidence from these earliest studies. Real-world data from the Cochrane Database of Systematic Reviews (CDSR) were collected. We…
Descriptors: Synthesis, Evidence, Decision Making, Reliability
Hu, Kaiyan; Zhao, Li; Zhou, Qi; Mei, Fan; Gao, Qianqian; Chen, Fei; Jiang, Mengyao; Zhao, Bing; Zhang, Weiyi; Kwong, Joey S. W.; Ma, Yuxia; Mou, Chenghua; Ma, Bin – Research Synthesis Methods, 2021
The author should give careful consideration to the study eligibility criteria of systematic reviews (SRs) and follow it after review protocol development to reduce the possibility of manipulation of inclusion. Our aim was to investigate the prevalence of differences in study eligibility criteria between non-Cochrane SRs and their pre-registered…
Descriptors: Eligibility, Reliability, Criteria, Literature Reviews
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
A. E. Ades; Nicky J. Welton; Sofia Dias; David M. Phillippo; Deborah M. Caldwell – Research Synthesis Methods, 2024
Network meta-analysis (NMA) is an extension of pairwise meta-analysis (PMA) which combines evidence from trials on multiple treatments in connected networks. NMA delivers internally consistent estimates of relative treatment efficacy, needed for rational decision making. Over its first 20 years NMA's use has grown exponentially, with applications…
Descriptors: Network Analysis, Meta Analysis, Medicine, Clinical Experience
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
Zhipeng Hou; Elizabeth Tipton – Research Synthesis Methods, 2024
Literature screening is the process of identifying all relevant records from a pool of candidate paper records in systematic review, meta-analysis, and other research synthesis tasks. This process is time consuming, expensive, and prone to human error. Screening prioritization methods attempt to help reviewers identify most relevant records while…
Descriptors: Meta Analysis, Research Reports, Identification, Evaluation Methods
Mikkel Helding Vembye; James Eric Pustejovsky; Therese Deocampo Pigott – Research Synthesis Methods, 2024
Sample size and statistical power are important factors to consider when planning a research synthesis. Power analysis methods have been developed for fixed effect or random effects models, but until recently these methods were limited to simple data structures with a single, independent effect per study. Recent work has provided power…
Descriptors: Sample Size, Robustness (Statistics), Effect Size, Social Science Research
Jager, Nicolas W.; Newig, Jens; Challies, Edward; Kochskämper, Elisa; von Wehrden, Henrik – Research Synthesis Methods, 2022
Meta-analytical methods face particular challenges in research fields such as social and political research, where studies often rest primarily on qualitative and case study research. In such contexts, where research findings are less standardized and amenable to structured synthesis, the case survey method has been proposed as a means of data…
Descriptors: Social Sciences, Meta Analysis, Case Studies, Validity
Nuijten, Michèle B.; Polanin, Joshua R. – Research Synthesis Methods, 2020
We present the R package and web app "statcheck" to automatically detect statistical reporting inconsistencies in primary studies and meta-analyses. Previous research has shown a high prevalence of reported p-values that are inconsistent--meaning a re-calculated p-value, based on the reported test statistic and degrees of freedom, does…
Descriptors: Meta Analysis, Statistical Analysis, Reliability, Replication (Evaluation)
Saluja, Ronak; Cheng, Sierra; delos Santos, Keemo Althea; Chan, Kelvin K. W. – Research Synthesis Methods, 2019
Objective: Various statistical methods have been developed to estimate hazard ratios (HRs) from published Kaplan-Meier (KM) curves for the purpose of performing meta-analyses. The objective of this study was to determine the reliability, accuracy, and precision of four commonly used methods by Guyot, Williamson, Parmar, and Hoyle and Henley.…
Descriptors: Meta Analysis, Reliability, Accuracy, Randomized Controlled Trials
Donegan, Sarah; Dias, Sofia; Welton, Nicky J. – Research Synthesis Methods, 2019
When numerous treatments exist for a disease (Treatments 1, 2, 3, etc), network meta-regression (NMR) examines whether each relative treatment effect (eg, mean difference for 2 vs 1, 3 vs 1, and 3 vs 2) differs according to a covariate (eg, disease severity). Two consistency assumptions underlie NMR: consistency of the treatment effects at the…
Descriptors: Reliability, Regression (Statistics), Outcomes of Treatment, Statistical Analysis
Hartwig, Fernando P.; Davey Smith, George; Schmidt, Amand F.; Sterne, Jonathan A. C.; Higgins, Julian P. T.; Bowden, Jack – Research Synthesis Methods, 2020
Meta-analyses based on systematic literature reviews are commonly used to obtain a quantitative summary of the available evidence on a given topic. However, the reliability of any meta-analysis is constrained by that of its constituent studies. One major limitation is the possibility of small-study effects, when estimates from smaller and larger…
Descriptors: Meta Analysis, Research Methodology, Effect Size, Robustness (Statistics)
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