Binomial Regression with Misclassification

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Motivated by a study of human papillomavirus infection in women, we present a Bayesian binomial regression analysis in which the response is subject to an unconstrained misclassification process. Our iterative approach provides inferences for the parameters that describe the relationships of the covariates with the response and for the misclassification probabilities. Furthermore, our approach applies to any meaningful generalized linear model, making model selection possible. Finally, it is straightforward to extend it to multinomial settings.

Keywords: Bayesian analysis; Binomial regression; Generalized linear model; Misclassification

Document Type: Research Article


Affiliations: 1: Instituto Superior Técnico, e Centro de Matemática e Aplicações, Universidade Técnica de Lisboa, Portugal 2: Department of Epidemiology and Biostatistics, University of California, San Francisco, California, U.S.A.

Publication date: September 1, 2003

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