In:
Scandinavian Journal of Statistics, Wiley, Vol. 34, No. 4 ( 2007-12), p. 870-895
Abstract:
Abstract. This paper describes our studies on non‐parametric maximum‐likelihood estimators in a semiparametric mixture model for competing‐risks data, in which proportional hazards models are specified for failure time models conditional on cause and a multinomial model is specified for the marginal distribution of cause conditional on covariates. We provide a verifiable identifiability condition and, based on it, establish an asymptotic profile likelihood theory for this model. We also provide efficient algorithms for the computation of the non‐parametric maximum‐likelihood estimate and its asymptotic variance. The success of this method is demonstrated in simulation studies and in the analysis of Taiwan severe acute respiratory syndrome data.
Type of Medium:
Online Resource
ISSN:
0303-6898
,
1467-9469
DOI:
10.1111/sjos.2007.34.issue-4
DOI:
10.1111/j.1467-9469.2007.00567.x
Language:
English
Publisher:
Wiley
Publication Date:
2007
detail.hit.zdb_id:
186702-7
detail.hit.zdb_id:
1466951-1
