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.
Dokumententyp: | Paper |
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Keywords: | threshold limiting value (TLV), segmented regression, measurement error, MCMC |
Fakultät: | Mathematik, Informatik und Statistik > Statistik > Sonderforschungsbereich 386
Sonderforschungsbereiche > Sonderforschungsbereich 386 |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
URN: | urn:nbn:de:bvb:19-epub-1537-7 |
Sprache: | Englisch |
Dokumenten ID: | 1537 |
Datum der Veröffentlichung auf Open Access LMU: | 04. Apr. 2007 |
Letzte Änderungen: | 04. Nov. 2020, 12:45 |