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Titolo:
PREDICTING SURVIVAL PROBABILITIES WITH SEMIPARAMETRIC TRANSFORMATION MODELS
Autore:
CHENG SC; WEI LJ; YING Z;
Indirizzi:
UNIV TEXAS,MD ANDERSON CANCER CTR,DEPT BIOMATH HOUSTON TX 77030 HARVARD UNIV,DEPT BIOSTAT BOSTON MA 02115 RUTGERS STATE UNIV,DEPT STAT PISCATAWAY NJ 08855
Titolo Testata:
Journal of the American Statistical Association
fascicolo: 437, volume: 92, anno: 1997,
pagine: 227 - 235
Fonte:
ISI
Lingua:
ENG
Soggetto:
PROPORTIONAL HAZARDS MODEL; CONFIDENCE BANDS; CENSORED-DATA; REGRESSION-MODEL;
Keywords:
GAUSSIAN PROCESS; MARTINGALE; PROPORTIONAL HAZARDS MODEL; PROPORTIONAL ODDS MODEL; WEAK CONVERGENCE;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
Science Citation Index Expanded
Citazioni:
25
Recensione:
Indirizzi per estratti:
Citazione:
S.C. Cheng et al., "PREDICTING SURVIVAL PROBABILITIES WITH SEMIPARAMETRIC TRANSFORMATION MODELS", Journal of the American Statistical Association, 92(437), 1997, pp. 227-235

Abstract

Prediction of survival probabilities for future patients is one of the-main goals of fitting survival data with regression models. In this article we consider a large class of semiparametric transformation models, which includes the well-known proportional hazards and proportional odds models, for the analysis of failure time data. Specifically, we propose pointwise and simultaneous confidence interval procedures for the survival probability of future patients with specific covariates. These procedures can be easily implemented through;simulation and are illustrated with the data from two well-known clinical studies.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 24/09/20 alle ore 05:03:32