Frailty models for arbitrarily censored and truncated data

In this paper, we propose a frailty model for statistical inference in the case where we are faced with arbitrarily censored and truncated data. Our results extend those of Alioum and Commenges (1996), who developed a method of fitting a proportional hazards model to data of this kind. We discuss th...

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Bibliographic Details
Published in:Lifetime data analysis 2004-12, Vol.10 (4), p.369-388
Main Authors: Huber-Carol, Catherine, Vonta, Ilia
Format: Article
Language:English
Subjects:
Acquired immune deficiency syndrome
Acquired Immunodeficiency Syndrome - etiology
Acquired Immunodeficiency Syndrome - mortality
AIDS
Data Interpretation, Statistical
Female
Humans
Life Tables
Male
Mathematical models
Maximum likelihood method
Models, Statistical
Proportional Hazards Models
Sensitivity and Specificity
Statistical analysis
Studies
Survival Analysis
Transfusion Reaction
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Summary:In this paper, we propose a frailty model for statistical inference in the case where we are faced with arbitrarily censored and truncated data. Our results extend those of Alioum and Commenges (1996), who developed a method of fitting a proportional hazards model to data of this kind. We discuss the identifiability of the regression coefficients involved in the model which are the parameters of interest, as well as the identifiability of the baseline cumulative hazard function of the model which plays the role of the infinite dimensional nuisance parameter. We illustrate our method with the use of simulated data as well as with a set of real data on transfusion-related AIDS.
ISSN:1380-7870
1572-9249
DOI:10.1007/s10985-004-4773-y