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Titolo:
Hierarchical proportional hazards regression models for highly stratified data
Autore:
Carlin, BP; Hodges, JS;
Indirizzi:
Univ Minnesota, Sch Publ Hlth, Div Biostat, Minneapolis, MN 55455 USA UnivMinnesota Minneapolis MN USA 55455 iostat, Minneapolis, MN 55455 USA
Titolo Testata:
BIOMETRICS
fascicolo: 4, volume: 55, anno: 1999,
pagine: 1162 - 1170
SICI:
0006-341X(199912)55:4<1162:HPHRMF>2.0.ZU;2-K
Fonte:
ISI
Lingua:
ENG
Soggetto:
BAYESIAN-ANALYSIS; TIME DATA; TRIALS;
Keywords:
baseline hazard function; Bayesian methods; Cox model; Markov chain Monte Carlo; partial likelihood;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Life Sciences
Citazioni:
23
Recensione:
Indirizzi per estratti:
Indirizzo: Carlin, BP Univ Minnesota, Sch Publ Hlth, Div Biostat, Box 303 Mayo Bldg, Minneapolis, MN 55455 USA Univ Minnesota Box 303 Mayo Bldg Minneapolis MN USA 55455 5 USA
Citazione:
B.P. Carlin e J.S. Hodges, "Hierarchical proportional hazards regression models for highly stratified data", BIOMETRICS, 55(4), 1999, pp. 1162-1170

Abstract

In clinical trials conducted over several data collection centers, the most common statistically defensible analytic method, a stratified Cox model analysis, suffers from two important defects. First, identification of unitsthat are outlying with respect to the baseline hazard is awkward since this hazard is implicit (rather than explicit) in the Cox partial likelihood. Second land more seriously), identification of modest treatment effects is often difficult since the model fails to acknowledge any similarity across the strata. We consider a number of hierarchical modeling approaches that preserve the integrity of the stratified design while offering a middle ground between traditional stratified and unstratified analyses. We investigateboth fully parametric (Weibull) and semiparametric models, the latter based not on the Cox model but on an extension of an idea by Gelfand and Mallick (1995, Biometrics 51, 843-852), which models the integrated baseline hazard as a mixture of monotone functions. We illustrate the methods using datafrom a recent multicenter AIDS clinical trial, comparing their ease of use, interpretation, and degree of robustness with respect to estimates of both the unit-specific baseline hazards and the treatment effect.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 25/11/20 alle ore 09:06:04