Semiparametric bayes' proportional odds models for current status data with underreporting.
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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Related Subject Headings
- Statistics & Probability
- Risk Factors
- Regression Analysis
- Proportional Hazards Models
- Odds Ratio
- Leiomyoma
- Humans
- Female
- Epidemiologic Studies
- Data Interpretation, Statistical
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Statistics & Probability
- Risk Factors
- Regression Analysis
- Proportional Hazards Models
- Odds Ratio
- Leiomyoma
- Humans
- Female
- Epidemiologic Studies
- Data Interpretation, Statistical