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Titolo: A BAYESIANANALYSIS OF MIXED SURVIVAL MODELS
Autore: DUCROCQ V; CASELLA G;
 Indirizzi:
 INRA,GENET QUANTITAT & APPL STN F78352 JOUY EN JOSAS FRANCE CORNELL UNIV,DEPT ANIM SCI ITHACA NY 14852 CORNELL UNIV,BIOMETR UNIT ITHACA NY 14852
 Titolo Testata:
 Genetics selection evolution
fascicolo: 6,
volume: 28,
anno: 1996,
pagine: 505  529
 SICI:
 0999193X(1996)28:6<505:ABOMSM>2.0.ZU;26
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 MAXIMUMLIKELIHOOD; PRODUCTIVE LIFE; EM ALGORITHM; DAIRYCOWS; INFERENCE; APPROXIMATIONS; DISTRIBUTIONS; FRAILTY; LENGTH; TRAITS;
 Keywords:
 SURVIVAL ANALYSIS; MIXED MODEL; VARIANCE COMPONENT ESTIMATION; BAYESIAN ANALYSIS; PROPORTIONAL HAZARDS MODEL;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Science Citation Index Expanded
 Science Citation Index Expanded
 Citazioni:
 55
 Recensione:
 Indirizzi per estratti:



 Citazione:
 V. Ducrocq e G. Casella, "A BAYESIANANALYSIS OF MIXED SURVIVAL MODELS", Genetics selection evolution, 28(6), 1996, pp. 505529
Abstract
In proportional hazards models, the hazard of an animal lambda(t), ie, its probability of dying or being culled at time t given it is aliveprior to t, is described as lambda(t) = lambda(0)(t)e(w'theta) where lambda(0)(t) is a 'baseline' hazard function and e(w'theta) representsthe effect of covariates w on culling rate. A distribution can be attached to elements s(q) in theta, identifying, for example, genetic effects and leading to mixed survival models, also called 'frailty' models. To estimate the parameters tau of the distribution of frailty terms, a Bayesian analysis is proposed. Inferences are drawn from the marginal posterior density pi(tau) which can be derived from the joint posterior density via Laplacian integration, a powerful technique related to saddlepoint approximations. The validity of this technique is shownhere on simulated examples by comparing the resulting approximate pi(tau) to the one obtained by algebraic integration. This exact calculation is feasible in very specific cases only, whereas the saddlepoint approximation can be applied to situations where Xo(t) is arbitrary (Cox models) or parametric (eg, Weibull), where the frailty terms are correlated through a known relationship matrix, or in more general modelswith stratification and/or timedependent covariates. The influence of the censoring rate and the data structure is also illustrated.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 04/12/20 alle ore 13:12:07