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Diagnostic test; Generalized linear mixed model; Missing data; Gold standard; Meta-analysis; Bayesian hierarchical model
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Full-Text Articles in Statistical Models
Random Effects Models In A Meta-Analysis Of The Accuracy Of Diagnostic Tests Within A Gold Standard In The Presence Of Missing Data, Haitao Chu, Sining Chen, Thomas A. Louis
Random Effects Models In A Meta-Analysis Of The Accuracy Of Diagnostic Tests Within A Gold Standard In The Presence Of Missing Data, Haitao Chu, Sining Chen, Thomas A. Louis
Johns Hopkins University, Dept. of Biostatistics Working Papers
In evaluating the accuracy of diagnosis tests, it is common to apply two imperfect tests jointly or sequentially to a study population. In a recent meta-analysis of the accuracy of microsatellite instability testing (MSI) and traditional mutation analysis (MUT) in predicting germline mutations of the mismatch repair (MMR) genes, a Bayesian approach (Chen, Watson, and Parmigiani 2005) was proposed to handle missing data resulting from partial testing and the lack of a gold standard. In this paper, we demonstrate an improved estimation of the sensitivities and specificities of MSI and MUT by using a nonlinear mixed model and a Bayesian …