2016
DOI: 10.1002/sim.6996
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Bayesian adjustment for the misclassification in both dependent and independent variables with application to a breast cancer study

Abstract: In this paper, we propose a Bayesian method to address misclassification errors in both independent and dependent variables. Our work is motivated by a study of women who have experienced new breast cancers on two separate occasions. We call both cancers primary, because the second is usually not considered as the result of a metastasis spreading from the first. Hormone receptors (HRs) are important in breast cancer biology, and it is well recognized that the measurement of HR status is subject to errors. This… Show more

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(1 citation statement)
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“…Equation (2) is widely used when one needs to correct for misclassification in the response in a logistic regression. 1217 It can also be seen as a generalization of the logistic regression model. Rousseeuw and Christmann 18 illustrate this model as in Figure 1 and refer to it as the hidden logistic regression model because the true response T i is hidden by the misclassification model in the top part of Figure 1.…”
Section: Methodsmentioning
confidence: 99%
“…Equation (2) is widely used when one needs to correct for misclassification in the response in a logistic regression. 1217 It can also be seen as a generalization of the logistic regression model. Rousseeuw and Christmann 18 illustrate this model as in Figure 1 and refer to it as the hidden logistic regression model because the true response T i is hidden by the misclassification model in the top part of Figure 1.…”
Section: Methodsmentioning
confidence: 99%