Semiparametric Bayes' Proportional Odds Models for Current Status Data with Underreporting
Article first published online: 22 DEC 2010
© 2010, The International Biometric Society
Volume 67, Issue 3, pages 1111–1118, September 2011
How to Cite
Wang, L. and Dunson, D. B. (2011), Semiparametric Bayes' Proportional Odds Models for Current Status Data with Underreporting. Biometrics, 67: 1111–1118. doi: 10.1111/j.1541-0420.2010.01532.x
- Issue published online: 14 SEP 2011
- Article first published online: 22 DEC 2010
- Received January 2009. Revised August 2010. Accepted September 2010.
- Interval censored;
- Measurement error;
- Monotone splines;
- Proportional odds model;
- Survival analysis;
- Uterine fibroids
Summary 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.