Proportional hazards models: a latent competing risk approach

被引：20

作者：

Gelfand, AE

Ghosh, SK

Christiansen, C

Soumerai, SB

McLaughlin, TJ

机构：

[1] Univ Connecticut, Coll Liberal Arts & Sci, Dept Stat, Storrs, CT 06269 USA

[2] N Carolina State Univ, Raleigh, NC USA

[3] Harvard Univ, Sch Med, Boston, MA 02115 USA

[4] Harvard Pilgrim Hlth Care, Boston, MA USA

来源：

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS | 2000年 / 49卷

关键词：

censoring; competing risk; data augmentation; semiparametric regression;

D O I：

10.1111/1467-9876.00199

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We propose a novel semiparametric version of the widely used proportional hazards survival model. Features include an arbitrarily rich class of continuous base-line hazards, an attractive epidemiological interpretation of the hazard as a latent competing risk model and trivial handling of censoring. Models are fitted by using a data augmentation scheme. The methodology is applied to a data set recording times to first hospitalization following clinical diagnosis of acquired immune deficiency syndrome for a sample of 169 patients.

引用

页码：385 / 397

页数：13

共 28 条

[1] Aitkin M., 1989, STAT MODELLING GLIM
[2] [Anonymous], APPL STAT, DOI DOI 10.2307/2347565
[3] ARJAS E, 1994, STAT SINICA, V4, P505
[4] COVARIANCE ANALYSIS OF CENSORED SURVIVAL DATA
BRESLOW, N
[J]. BIOMETRICS, 1974, 30 (01) : 89 - 99
[5] CARLIN BP, 1995, J ROY STAT SOC B MET, V57, P473
[6] Cox D. R, 1962, RENEWAL THEORY
[7] Cox D. R., 1984, ANAL SURVIVAL DATA
[8] COX DR, 1972, J R STAT SOC B, V34, P187
[9] BAYESIAN-INFERENCE FOR GENERALIZED LINEAR AND PROPORTIONAL HAZARDS MODELS VIA GIBBS SAMPLING
DELLAPORTAS, P
SMITH, AFM
[J]. APPLIED STATISTICS-JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C, 1993, 42 (03): : 443 - 459
[10] MAXIMUM LIKELIHOOD FROM INCOMPLETE DATA VIA EM ALGORITHM
DEMPSTER, AP
LAIRD, NM
RUBIN, DB
[J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, 1977, 39 (01): : 1 - 38

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