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de Jong, Valentijn M. T.; Campbell, Harlan; Maxwell, Lauren; Jaenisch, Thomas; Gustafson, Paul; Debray, Thomas P. A. – Research Synthesis Methods, 2023
A common problem in the analysis of multiple data sources, including individual participant data meta-analysis (IPD-MA), is the misclassification of binary variables. Misclassification may lead to biased estimators of model parameters, even when the misclassification is entirely random. We aimed to develop statistical methods that facilitate…
Descriptors: Classification, Meta Analysis, Bayesian Statistics, Evaluation Methods
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
Cerullo, Enzo; Jones, Hayley E.; Carter, Olivia; Quinn, Terry J.; Cooper, Nicola J.; Sutton, Alex J. – Research Synthesis Methods, 2022
Standard methods for the meta-analysis of medical tests, without assuming a gold standard, are limited to dichotomous data. Multivariate probit models are used to analyse correlated dichotomous data, and can be extended to model ordinal data. Within the context of an imperfect gold standard, they have previously been used for the analysis of…
Descriptors: Meta Analysis, Test Format, Medicine, Standards
Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca – Research Synthesis Methods, 2022
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…
Descriptors: Patients, Medical Research, Comparative Analysis, Outcomes of Treatment
Matsushima, Yuki; Noma, Hisashi; Yamada, Tomohide; Furukawa, Toshi A. – Research Synthesis Methods, 2020
Meta-analyses of diagnostic test accuracy (DTA) studies have been gaining prominence in research in clinical epidemiology and health technology development. In these DTA meta-analyses, some studies may have markedly different characteristics from the others and potentially be inappropriate to include. The inclusion of these "outlying"…
Descriptors: Diagnostic Tests, Clinical Diagnosis, Accuracy, Meta Analysis
Xie, Xuanqian; Sinclair, Alison; Dendukuri, Nandini – Research Synthesis Methods, 2017
Background: "Streptococcus pneumoniae" (SP) pneumonia is often treated empirically as diagnosis is challenging because of the lack of a perfect test. Using BinaxNOW-SP, a urinary antigen test, as an add-on to standard cultures may not only increase diagnostic yield but also increase costs. Objective: To estimate the sensitivity and…
Descriptors: Accuracy, Cost Effectiveness, Medical Services, Diseases
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