Math @ Duke
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Publications [#257970] of David B. Dunson
search arxiv.org.Papers Published
- Wang, L; Dunson, DB, Semiparametric bayes' proportional odds models for current status data with underreporting.,
Biometrics, vol. 67 no. 3
(September, 2011),
pp. 1111-1118, ISSN 0006-341X [doi]
(last updated on 2024/04/24)
Abstract: Current status data are a type of interval-censored event time data in which all the individuals are either left or right censored. For example, our motivation is drawn from a cross-sectional study, which measured whether or not fibroid onset had occurred by the age of an ultrasound exam for each woman. We propose a semiparametric Bayesian proportional odds model in which the baseline event time distribution is estimated nonparametrically by using adaptive monotone splines in a logistic regression model and the potential risk factors are included in the parametric part of the mean structure. The proposed approach has the advantage of being straightforward to implement using a simple and efficient Gibbs sampler, whereas alternative semiparametric Bayes' event time models encounter problems for current status data. The model is generalized to allow systematic underreporting in a subset of the data, and the methods are applied to an epidemiologic study of uterine fibroids.
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