A Cautionary Note on the Robustness of Latent Class Models for Estimating Diagnostic Error without a Gold Standard
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Publication:3442973
DOI10.1111/j.0006-341X.2004.00187.xzbMath1274.62486OpenAlexW2121856130WikidataQ52963671 ScholiaQ52963671MaRDI QIDQ3442973
Publication date: 25 May 2007
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.0006-341x.2004.00187.x
Applications of statistics to biology and medical sciences; meta analysis (62P10) Diagnostics, and linear inference and regression (62J20)
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Uses Software
Cites Work
- Misspecified maximum likelihood estimates and generalised linear mixed models
- Bayesian Approaches to Modeling the Conditional Dependence Between Multiple Diagnostic Tests
- Latent Class Modeling Approaches for Assessing Diagnostic Error without a Gold Standard: With Applications to p53 Immunohistochemical Assays in Bladder Tumors
- Estimating the Error Rates of Diagnostic Tests
- A Biomedical Application of Latent Class Models with Random Effects
- Random Effects Models in Latent Class Analysis for Evaluating Accuracy of Diagnostic Tests
- Latent Variable Modeling of Diagnostic Accuracy
- Using Latent Class Models to Characterize and Assess Relative Error in Discrete Measurements
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