Semiparametric bayes' proportional odds models for current status data with underreporting

Biometrics. 2011 Sep;67(3):1111-8. doi: 10.1111/j.1541-0420.2010.01532.x. Epub 2010 Dec 22.


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.

MeSH terms

  • Bayes Theorem
  • Data Interpretation, Statistical*
  • Epidemiologic Studies*
  • Female
  • Humans
  • Leiomyoma
  • Odds Ratio
  • Proportional Hazards Models
  • Regression Analysis*
  • Risk Factors