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A Semiparametric hierarchical method for a regression model with an interval-censored covariate

A Semiparametric hierarchical method for a regression model with an interval-censored covariate
 
Calle, M. Luz ; Gómez, Guadalupe
2005

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Enllaç permanent: http://hdl.handle.net/10854/3056
 
Versió de l'editor: https://doi.org/10.1111/j.1467-842X.2005.00400.x/pdf
 

Abstract

A Bayesian framework is proposed for analysing regression models in which one of the covariates is interval-censored. Such a situation was encountered in an AIDS clinical trial in which the goal was to examine the association between delays in initiating a new treatment after Indinavir failure and the subsequent viral load level ...»»»»
A Bayesian framework is proposed for analysing regression models in which one of the covariates is interval-censored. Such a situation was encountered in an AIDS clinical trial in which the goal was to examine the association between delays in initiating a new treatment after Indinavir failure and the subsequent viral load level of patients at the time of enrolment into the new treatment. The new method uses a mixture of Dirichlet processes allowing all the components in the model to be specified parametrically, except for the distribution of the interval-censored covariate, which is treated non-parametrically. The paper explains the proposed method for the linear regression model in detail. The performance of the method is assessed by simulations and illustrated using the AIDS clinical trial.^^^^

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Article

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(c) Wiley [The definitive version is available at www3.interscience.wiley.com]

Citation:

Calle Rosingana, M. L., & Gomez, G. (2005). A semiparametric hierarchical method for a regression model with an interval-censored covariate. Australian & New Zealand Journal of Statistics, 47(3), 351-364.