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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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Harari, Ofir; Soltanifar, Mohsen; Cappelleri, Joseph C.; Verhoek, Andre; Ouwens, Mario; Daly, Caitlin; Heeg, Bart – Research Synthesis Methods, 2023
Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this…
Descriptors: Networks, Network Analysis, Meta Analysis, Evaluation Methods
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Song, Yue; Sun, Feng; Redline, Susan; Wang, Rui – Research Synthesis Methods, 2020
Meta-analyses of clinical trials typically focus on one outcome at a time. However, treatment decision-making depends on an overall assessment of outcomes balancing benefit in various domains and potential risks. This calls for meta-analysis methods for combined outcomes that encompass information from different domains. When individual patient…
Descriptors: Meta Analysis, Patients, Data, Outcomes of Treatment
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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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Hinchliffe, Sally R.; Crowther, Michael J.; Phillips, Robert S.; Sutton, Alex J. – Research Synthesis Methods, 2013
An individual diagnostic accuracy study rarely provides enough information to make conclusive recommendations about the accuracy of a diagnostic test; particularly when the study is small. Meta-analysis methods provide a way of combining information from multiple studies, reducing uncertainty in the result and hopefully providing substantial…
Descriptors: Meta Analysis, Design, Diagnostic Tests, Accuracy
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Wu, Meng-Jia; Becker, Betsy Jane – Research Synthesis Methods, 2013
Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported…
Descriptors: Regression (Statistics), Correlation, Research Methodology, Accuracy
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Trikalinos, Thomas A.; Hoaglin, David C.; Small, Kevin M.; Terrin, Norma; Schmid, Christopher H. – Research Synthesis Methods, 2014
Existing methods for meta-analysis of diagnostic test accuracy focus primarily on a single index test. We propose models for the joint meta-analysis of studies comparing multiple index tests on the same participants in paired designs. These models respect the grouping of data by studies, account for the within-study correlation between the tests'…
Descriptors: Meta Analysis, Diagnostic Tests, Accuracy, Comparative Analysis