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Pedder, Hugo; Boucher, Martin; Dias, Sofia; Bennetts, Margherita; Welton, Nicky J. – Research Synthesis Methods, 2020
Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies…
Descriptors: Simulation, Randomized Controlled Trials, Meta Analysis, Comparative Analysis
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Pedder, Hugo; Dias, Sofia; Bennetts, Margherita; Boucher, Martin; Welton, Nicky J. – Research Synthesis Methods, 2019
Background: Model-based meta-analysis (MBMA) is increasingly used to inform drug-development decisions by synthesising results from multiple studies to estimate treatment, dose-response, and time-course characteristics. Network meta-analysis (NMA) is used in Health Technology Appraisals for simultaneously comparing effects of multiple treatments,…
Descriptors: Meta Analysis, Guidelines, Drug Therapy, Decision Making
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Horbach, Serge P. J. M. – Research Evaluation, 2021
The global COVID-19 pandemic has had a considerable impact on the scientific enterprise, including scholarly publication and peer-review practices. Several studies have assessed these impacts, showing among others that medical journals have strongly accelerated their review processes for COVID-19-related content. This has raised questions and…
Descriptors: Peer Evaluation, Periodicals, Medicine, Medical Research
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Moustgaard, Helene; Jones, Hayley E.; Savovic, Jelena; Clayton, Gemma L.; Sterne, Jonathan AC; Higgins, Julian PT; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2020
Randomized clinical trials underpin evidence-based clinical practice, but flaws in their conduct may lead to biased estimates of intervention effects and hence invalid treatment recommendations. The main approach to the empirical study of bias is to collate a number of meta-analyses and, within each, compare the results of trials with and without…
Descriptors: Epidemiology, Evidence, Medical Research, Intervention
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Leahy, Joy; Walsh, Cathal – Research Synthesis Methods, 2019
If IPD is available for some or all trials in a network meta-analysis (NMA), then incorporating this IPD into an NMA is routinely considered to be preferable. However, the situation often arises where a researcher has IPD for trials concerning a particular treatment (eg, from a sponsor) but none for other trials. Therefore, one can reweight the…
Descriptors: Comparative Analysis, Meta Analysis, Bayesian Statistics, Network Analysis
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Kosch, Robin; Jung, Klaus – Research Synthesis Methods, 2019
Research synthesis, eg, by meta-analysis, is more and more considered in the area of high-dimensional data from molecular research such as gene and protein expression data, especially because most studies and experiments are performed with very small sample sizes. In contrast to most clinical and epidemiological trials, raw data are often…
Descriptors: Genetics, Meta Analysis, Molecular Structure, Scientific Research
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Stevens, John W.; Fletcher, Christine; Downey, Gerald; Sutton, Anthea – Research Synthesis Methods, 2018
A network meta-analysis allows a simultaneous comparison between treatments evaluated in randomised controlled trials that share at least one treatment with at least one other study. Estimates of treatment effects may be required for treatments across disconnected networks of evidence, which requires a different statistical approach and modelling…
Descriptors: Meta Analysis, Network Analysis, Comparative Analysis, Outcomes of Treatment
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Brunton, Ginny; Webbe, James; Oliver, Sandy; Gale, Chris – Research Synthesis Methods, 2020
Trials evaluating the same interventions rarely measure or report identical outcomes. This limits the possibility of aggregating effect sizes across studies to generate high-quality evidence through systematic reviews and meta-analyses. To address this problem, core outcome sets (COS) establish agreed sets of outcomes to be used in all future…
Descriptors: Intervention, Outcome Measures, Effect Size, Qualitative Research
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Schmitz, Tom; Bukowski, Mark; Koschmieder, Steffen; Schmitz-Rode, Thomas; Farkas, Robert – Research Synthesis Methods, 2019
Launching biomedical innovations based on clinical demands instead of translating basic research findings to practice reduces the risk that the results will not fit the clinical routine. To realize this type of innovation, a meta-analysis of the body of research is necessary to reveal demand-matching concepts. However, both the data deluge and the…
Descriptors: Innovation, Biomedicine, Medical Research, Meta Analysis
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Langan, Dean; Higgins, Julian P. T.; Simmonds, Mark – Research Synthesis Methods, 2017
Random-effects meta-analysis methods include an estimate of between-study heterogeneity variance. We present a systematic review of simulation studies comparing the performance of different estimation methods for this parameter. We summarise the performance of methods in relation to estimation of heterogeneity and of the overall effect estimate,…
Descriptors: Meta Analysis, Simulation, Comparative Analysis, Intervals
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Sutton, Anthea; Galvan De La Cruz, Maria Carmen; Leaviss, Joanna; Booth, Andrew – Research Synthesis Methods, 2018
Introduction: Registration and publication of trial protocols has become increasingly important and a requirement in some sources of funding and publication. Increased access to protocols yields many potential benefits, but there are issues regarding identification of published protocols. The aim of this investigation is to compare methods of…
Descriptors: Comparative Analysis, Medical Research, Research Methodology, Outcomes of Treatment
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Biocic, Marina; Fidahic, Mahir; Cikes, Karla; Puljak, Livia – Research Synthesis Methods, 2019
Background: It has been reported that information sources searched in systematic reviews (SRs) are insufficiently comprehensive. We analyzed information sources used in SRs, as well as how up-to-date were the searches. Methods: We searched PubMed and the Cochrane Database of Systematic Reviews (CDSR) through Wiley from 2012 to 2016 to find SRs of…
Descriptors: Pain, Case Studies, Anesthesiology, Databases
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Kontopantelis, Evangelos – Research Synthesis Methods, 2018
Background: Individual patient data (IPD) meta-analysis allows for the exploration of heterogeneity and can identify subgroups that most benefit from an intervention (or exposure), much more successfully than meta-analysis of aggregate data. One-stage or two-stage IPD meta-analysis is possible, with the former using mixed-effects regression models…
Descriptors: Patients, Medical Research, Meta Analysis, Intervention
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Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua – Research Synthesis Methods, 2017
This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum…
Descriptors: Medical Research, Regression (Statistics), Comparative Analysis, Maximum Likelihood Statistics
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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
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