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Mavridis, Dimitris; White, Ian R. – Research Synthesis Methods, 2020
Missing data result in less precise and possibly biased effect estimates in single studies. Bias arising from studies with incomplete outcome data is naturally propagated in a meta-analysis. Conventional analysis using only individuals with available data is adequate when the meta-analyst can be confident that the data are missing at random (MAR)…
Descriptors: Meta Analysis, Data Analysis, Statistical Bias, Outcome Measures
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Stoll, Carolyn R. T.; Izadi, Sonya; Fowler, Susan; Green, Paige; Suls, Jerry; Colditz, Graham A. – Research Synthesis Methods, 2019
Background: Although dual independent review of search results by two reviewers is generally recommended for systematic reviews, there are not consistent recommendations regarding the timing of the use of the second reviewer. This study compared the use of a complete dual review approach, with two reviewers in both the title/abstract screening…
Descriptors: Literature Reviews, Researchers, Research Problems, Research Methodology
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Efthimiou, Orestis; White, Ian R. – Research Synthesis Methods, 2020
Standard models for network meta-analysis simultaneously estimate multiple relative treatment effects. In practice, after estimation, these multiple estimates usually pass through a formal or informal selection procedure, eg, when researchers draw conclusions about the effects of the best performing treatment in the network. In this paper, we…
Descriptors: Models, Meta Analysis, Network Analysis, Simulation
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Nejstgaard, Camilla Hansen; Lundh, Andreas; Abdi, Suhayb; Clayton, Gemma; Gelle, Mustafe Hassan Adan; Laursen, David Ruben Teindl; Olorisade, Babatunde Kazeem; Savovic, Jelena; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2022
Randomised trials are often funded by commercial companies and methodological studies support a widely held suspicion that commercial funding may influence trial results and conclusions. However, these studies often have a risk of confounding and reporting bias. The risk of confounding is markedly reduced in meta-epidemiological studies that…
Descriptors: Medical Research, Randomized Controlled Trials, Corporations, Financial Support
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Wang, Qianying; Liao, Jing; Lapata, Mirella; Macleod, Malcolm – Research Synthesis Methods, 2022
We sought to apply natural language processing to the task of automatic risk of bias assessment in preclinical literature, which could speed the process of systematic review, provide information to guide research improvement activity, and support translation from preclinical to clinical research. We use 7840 full-text publications describing…
Descriptors: Risk, Natural Language Processing, Medical Research, Networks
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Bender, Ralf; Friede, Tim; Koch, Armin; Kuss, Oliver; Schlattmann, Peter; Schwarzer, Guido; Skipka, Guido – Research Synthesis Methods, 2018
In systematic reviews, meta-analyses are routinely applied to summarize the results of the relevant studies for a specific research question. If one can assume that in all studies the same true effect is estimated, the application of a meta-analysis with common effect (commonly referred to as fixed-effect meta-analysis) is adequate. If…
Descriptors: Evidence, Synthesis, Meta Analysis, Research Problems
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Bom, Pedro R. D.; Rachinger, Heiko – Research Synthesis Methods, 2019
Publication bias distorts the available empirical evidence and misinforms policymaking. Evidence of publication bias is mounting in virtually all fields of empirical research. This paper proposes the endogenous kink (EK) meta-regression model as a novel method of publication bias correction. The EK method fits a piecewise linear meta-regression of…
Descriptors: Bias, Publications, Models, Regression (Statistics)
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Lin, Lifeng; Chu, Haitao – Research Synthesis Methods, 2018
In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of…
Descriptors: Bayesian Statistics, Multivariate Analysis, Meta Analysis, Correlation
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Vo, Tat-Thang; Porcher, Raphael; Chaimani, Anna; Vansteelandt, Stijn – Research Synthesis Methods, 2019
Case-mix heterogeneity across studies complicates meta-analyses. As a result of this, treatments that are equally effective on patient subgroups may appear to have different effectiveness on patient populations with different case mix. It is therefore important that meta-analyses be explicit for what patient population they describe the treatment…
Descriptors: Case Studies, Meta Analysis, Research Problems, Medical Research
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Tipton, Elizabeth; Pustejovsky, James E.; Ahmadi, Hedyeh – Research Synthesis Methods, 2019
Having surveyed the history and methods of meta-regression in a previous paper, in this paper, we review which and how meta-regression methods are applied in recent research syntheses. To do so, we reviewed studies published in 2016 across four leading research synthesis journals: "Psychological Bulletin," the "Journal of Applied…
Descriptors: Medical Research, Psychological Studies, Regression (Statistics), Journal Articles
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Franco, Juan Víctor Ariel; Garrote, Virginia Laura; Escobar Liquitay, Camila Micaela; Vietto, Valeria – Research Synthesis Methods, 2018
Objective: Search strategies are essential for the adequate retrieval of studies in a systematic review (SR). Our objective was to identify problems in the design and reporting of search strategies in a sample of new Cochrane SRs first published in The Cochrane Library in 2015. Study design and setting: We took a random sample of 70 new Cochrane…
Descriptors: Search Strategies, Literature Reviews, Online Searching, Intervention
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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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Freeman, S. C.; Fisher, D.; Tierney, J. F.; Carpenter, J. R. – Research Synthesis Methods, 2018
Background: Stratified medicine seeks to identify patients most likely to respond to treatment. Individual participant data (IPD) network meta-analysis (NMA) models have greater power than individual trials to identify treatment-covariate interactions (TCIs). Treatment-covariate interactions contain "within" and "across" trial…
Descriptors: Medical Research, Patients, Outcomes of Treatment, Meta Analysis
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Yoneoka, Daisuke; Henmi, Masayuki – Research Synthesis Methods, 2017
Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the…
Descriptors: Meta Analysis, Multivariate Analysis, Research Problems, Regression (Statistics)
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Friede, Tim; Röver, Christian; Wandel, Simon; Neuenschwander, Beat – Research Synthesis Methods, 2017
Meta-analyses in orphan diseases and small populations generally face particular problems, including small numbers of studies, small study sizes and heterogeneity of results. However, the heterogeneity is difficult to estimate if only very few studies are included. Motivated by a systematic review in immunosuppression following liver…
Descriptors: Meta Analysis, Diseases, Medical Research, Research Problems
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