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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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Kylie E. Hunter; Mason Aberoumand; Sol Libesman; James X. Sotiropoulos; Jonathan G. Williams; Jannik Aagerup; Rui Wang; Ben W. Mol; Wentao Li; Angie Barba; Nipun Shrestha; Angela C. Webster; Anna Lene Seidler – Research Synthesis Methods, 2024
Increasing concerns about the trustworthiness of research have prompted calls to scrutinise studies' Individual Participant Data (IPD), but guidance on how to do this was lacking. To address this, we developed the IPD Integrity Tool to screen randomised controlled trials (RCTs) for integrity issues. Development of the tool involved a literature…
Descriptors: Integrity, Randomized Controlled Trials, Participant Characteristics, Computer Software
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Miriam Hattle; Joie Ensor; Katie Scandrett; Marienke van Middelkoop; Danielle A. van der Windt; Melanie A. Holden; Richard D. Riley – Research Synthesis Methods, 2024
Individual participant data (IPD) meta-analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta-analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant-level…
Descriptors: Meta Analysis, Randomized Controlled Trials, Outcomes of Treatment, Evaluation Methods
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Daly, Caitlin H.; Maconachie, Ross; Ades, A. E.; Welton, Nicky J. – Research Synthesis Methods, 2022
Randomised controlled trials of cancer treatments typically report progression free survival (PFS) and overall survival (OS) outcomes. Existing methods to synthesise evidence on PFS and OS either rely on the proportional hazards assumption or make parametric assumptions which may not capture the diverse survival curve shapes across studies and…
Descriptors: Nonparametric Statistics, Randomized Controlled Trials, Evidence, Networks
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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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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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Wilson, Sandra Jo; Polanin, Joshua R.; Lipsey, Mark W. – Research Synthesis Methods, 2016
A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation…
Descriptors: Meta Analysis, Structural Equation Models, Correlation, Research Methodology
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Harrison, Sean; Jones, Hayley E.; Martin, Richard M.; Lewis, Sarah J.; Higgins, Julian P. T. – Research Synthesis Methods, 2017
Meta-analyses combine the results of multiple studies of a common question. Approaches based on effect size estimates from each study are generally regarded as the most informative. However, these methods can only be used if comparable effect sizes can be computed from each study, and this may not be the case due to variation in how the studies…
Descriptors: Meta Analysis, Sample Size, Effect Size, Comparative Analysis
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Robertson, Clare; Ramsay, Craig; Gurung, Tara; Mowatt, Graham; Pickard, Robert; Sharma, Pawana – Research Synthesis Methods, 2014
We describe our experience of using a modified version of the Cochrane risk of bias (RoB) tool for randomised and non-randomised comparative studies. Objectives: (1) To assess time to complete RoB assessment; (2) To assess inter-rater agreement; and (3) To explore the association between RoB and treatment effect size. Methods: Cochrane risk of…
Descriptors: Risk, Randomized Controlled Trials, Research Design, Comparative Analysis