A penalized likelihood approach for a progressive three-state model with censored and truncated data: application to AIDS

Biometrics
P Joly, D Commenges

Abstract

We consider the estimation of the intensity and survival functions for a continuous time progressive three-state semi-Markov model with intermittently observed data. The estimator of the intensity function is defined nonparametrically as the maximum of a penalized likelihood. We thus obtain smooth estimates of the intensity and survival functions. This approach can accommodate complex observation schemes such as truncation and interval censoring. The method is illustrated with a study of hemophiliacs infected by HIV. The intensity functions and the cumulative distribution functions for the time to infection and for the time to AIDS are estimated. Covariates can easily be incorporated into the model.

Citations

Feb 3, 2006·Biometrical Journal. Biometrische Zeitschrift·Yohann FoucherJean-Pierre Daurès
Nov 17, 2009·Biometrics·Andrew C Titman, Linda D Sharples
Feb 11, 2011·Biometrics·Andrew C Titman
Aug 6, 2009·Statistical Methods in Medical Research·Andrew C Titman, Linda D Sharples
May 14, 2014·Statistical Methods in Medical Research·Shaoceng Wei, Richard J Kryscio
Dec 6, 2017·Statistics in Medicine·Florence GillaizeauYohann Foucher
Jun 10, 2015·Statistical Methods in Medical Research·Florence GillaizeauYohann Foucher
Jan 1, 2016·Communications in Statistics. Case Studies, Data Analysis and Applications·Lijie WanRichard J Kryscio
Jun 4, 2002·Statistical Methods in Medical Research·D Commenges
Jun 4, 2002·Statistical Methods in Medical Research·Per Kragh Andersen, Niels Keiding
May 5, 2017·Statistics in Medicine·Yonas Ghebremichael-WeldeselassieC Paddy Farrington

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