Catalogo Articoli (Spogli Riviste)

OPAC HELP

Titolo:
Semiparametric regression analysis for clustered failure time data
Autore:
Cai, T; Wei, LJ; Wilcox, M;
Indirizzi:
Harvard Univ, Dept Biostat, Boston, MA 02115 USA Harvard Univ Boston MA USA 02115 Univ, Dept Biostat, Boston, MA 02115 USA Dana Farber Canc Inst, Boston, MA 02115 USA Dana Farber Canc Inst Boston MA USA 02115 Canc Inst, Boston, MA 02115 USA
Titolo Testata:
BIOMETRIKA
fascicolo: 4, volume: 87, anno: 2000,
pagine: 867 - 878
SICI:
0006-3444(200012)87:4<867:SRAFCF>2.0.ZU;2-G
Fonte:
ISI
Lingua:
ENG
Soggetto:
TRANSFORMATION MODELS; CENSORED-DATA; HAZARDS;
Keywords:
censoring; Gaussian process; Kaplan-Meier estimate; linear transformation model; prediction; proportional hazards model; proportional odds model;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Life Sciences
Physical, Chemical & Earth Sciences
Citazioni:
22
Recensione:
Indirizzi per estratti:
Indirizzo: Cai, T Harvard Univ, Dept Biostat, 655 Huntington Ave, Boston, MA 02115 USA Harvard Univ 655 Huntington Ave Boston MA USA 02115 n, MA 02115 USA
Citazione:
T. Cai et al., "Semiparametric regression analysis for clustered failure time data", BIOMETRIKA, 87(4), 2000, pp. 867-878

Abstract

Inference procedures based on the partial likelihood function for the Cox proportional hazards model have been generalised to the case in which the data consist of a large number of independent small groups of correlated failure time observations (Lee, Wei & Amato, 1992; Liang, Self & Chang, 1993; Cai & Prentice, 1997). However, the Cox model may not fit the data well. A class of linear transformation models, which includes the proportional hazards and odds models as special cases, has been studied extensively for univariate event times. In this paper, statistical methods to analyse such correlated observations are proposed for these models. We use the data from a recent study of the genetic aetiology of alcoholism to illustrate the new procedures for estimation, prediction and model selection.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 24/09/20 alle ore 05:04:09