Bayesian analysis of logistic regression with an unknown change point

Gössl, Christoff and Küchenhoff, Helmut (1999): Bayesian analysis of logistic regression with an unknown change point. Collaborative Research Center 386, Discussion Paper 148

Abstract

We discuss Bayesian estimation of a logistic regression model with an unknown threshold limiting value (TLV). In these models it is assumed that there is no effect of a covariate on the response under a certain unknown TLV. The estimation of these models with a focus on the TLV in a Bayesian context by Markov chain Monte Carlo (MCMC) methods is considered. We extend the model by accounting for measurement error in the covariate. The Bayesian solution is compared with the likelihood solution proposed by Kuechenhoff and Carroll (1997) using a data set concerning the relationship between dust concentration in the working place and the occurrence of chronic bronchitis.

• Item Type: Paper
• Keywords: threshold limiting value (TLV), segmented regression, measurement error, MCMC
• Faculties: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English