Generating data from improper distributions: application to Cox proportional hazards models with cure

Oulhaj, A; San Martin, E

Abstract

Cure rate models are survival models characterized by improper survivor distributions which occur when the cumulative distribution function, say F, of the survival times does not sum up to 1 (i.e. F(+)<1). The first objective of this paper is to provide a general approach to generate data from any improper distribution. An application to times to event data randomly drawn from improper distributions with proportional hazards is investigated using the semi-parametric proportional hazards model with cure obtained as a special case of the nonlinear transformation models in [Tsodikov, Semiparametric models: A generalized self-consistency approach, J. R. Stat. Soc. Ser. B 65 (2003), pp. 759-774]. The second objective of this paper is to show by simulations that the bias, the standard error and the mean square error of the maximum partial likelihood (PL) estimator of the hazard ratio as well as the statistical power based on the PL estimator strongly depend on the proportion of subjects in the whole population who will never experience the event of interest.

Más información

Título según WOS: Generating data from improper distributions: application to Cox proportional hazards models with cure
Título de la Revista: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
Volumen: 84
Número: 1
Editorial: TAYLOR & FRANCIS LTD
Fecha de publicación: 2014
Página de inicio: 204
Página final: 214
Idioma: English
URL: http://www.tandfonline.com/doi/abs/10.1080/00949655.2012.700714
DOI:

10.1080/00949655.2012.700714

Notas: ISI