Abstract #300473

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JSM 2003 Abstract #300473
Activity Number: 129
Type: Contributed
Date/Time: Monday, August 4, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #300473
Title: A Cautionary Note on the Robustness of Latent Class Models for Estimating Diagnostic Error without a Gold Standard
Author(s): Paul S. Albert*+ and Lori E. Dodd
Companies: National Cancer Institute and National Cancer Institute
Address: 15158 Callohan Ct., Silver Spring, MD, 20906-6134,
Keywords: diagnostic error ; misclassification ; correlated binary data
Abstract:

Modeling diagnostic error without a gold standard hs been an active area of biostatistical research. This talk discusses an inherent problem with these approaches. Namely, we show that when the conditional dependence between tests is misspecified, estimators of sensitivity and specificity can be asymptotically biased. Further, we demonstrate that, with small numbers of tests, likelihood comparisons to distinguish between different classes of models that specify different types of dependence structures may not identify the appropriate model.

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