Author： Roy Surupa
Publisher： Taylor & Francis Ltd
ISSN： 0361-0918
Source： Communications in Statistics: Simulation and Computation, Vol.41, Iss.9, 2012-10, pp. : 1623-1636
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Abstract
Often in longitudinal data arising out of epidemiologic studies, measurement error in covariates and/or classification errors in binary responses may be present. The goal of the present work is to develop a random effects logistic regression model that corrects for the classification errors in binary responses and/or measurement error in covariates. The analysis is carried out under a Bayesian set up. Simulation study reveals the effect of ignoring measurement error and/or classification errors on the estimates of the regression coefficients.
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