Latent diffusion models for survival analysis

被引：3

作者：

Roberts, Gareth O. ^{[1
]}

Sangalli, Laura M. ^{[2
]}

机构：

[1] Univ Warwick, Dept Stat, CRiSM, Coventry CV4 7AL, W Midlands, England

[2] Politecn Milan, Dipartimento Matemat, MOX, I-20133 Milan, Italy

来源：

BERNOULLI | 2010年 / 16卷 / 02期

关键词：

diffusion processes; parametrization of hierarchical models; survival analysis; PROPORTIONAL HAZARDS; DISTRIBUTIONS; INFERENCE;

D O I：

10.3150/09-BEJ217

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 consider Bayesian hierarchical models for survival analysis, where the survival times are modeled through an underlying diffusion process which determines the hazard rate. We show how these models can be efficiently treated by means of Markov chain Monte Carlo techniques.

引用

页码：435 / 458

页数：24

共 50 条

[41] Asymptotical analysis of semiparametric models in survival analysis and accelerated life testing
Bagdonavicius, V
Nikulin, M
STATISTICS, 1997, 29 (03) : 261 - 283
[42] New models and methods for survival analysis of experimental data
Semenchenko, Ganna V.
Yashin, Anatoli I.
Johnson, Thomas E.
Cypser, James W.
ADVANCES IN STATISTICAL METHODS FOR THE HEALTH SCIENCES: APPLICATIONS TO CANCER AND AIDS STUDIES, GENOME SEQUENCE ANALYSIS, AND SURVIVAL ANALYSIS, 2007, : 179 - +
[43] On a measure of information gain for regression models in survival analysis
Maucort-Boulch, Delphine
Roy, Pascal
Stare, Janez
JOURNAL OF APPLIED STATISTICS, 2014, 41 (12) : 2696 - 2708
[44] Latent Class Survival Models Linked by Principal Stratification to Investigate Heterogenous Survival Subgroups Among Individuals With Early-Stage Kidney Cancer
Egleston, Brian L.
Uzzo, Robert G.
Wong, Yu-Ning
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2017, 112 (518) : 534 - 546
[45] Normalised latent measure factor models
Beraha, Mario
Griffin, Jim E.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2023, 85 (04) : 1247 - 1270
[46] Combined learning models for survival analysis of patients with pulmonary hypertension
Foguem, Germaine Tchuente
Coulibaly, Lassana
Diamoutene, Abdoulaye
INTELLIGENT SYSTEMS WITH APPLICATIONS, 2024, 21
[47] Survival analysis of women with breast cancer: competing risk models
Ferraz, Rosemeire de Olanda
Moreira-Filho, Djalma de Carvalho
CIENCIA & SAUDE COLETIVA, 2017, 22 (11): : 3743 - 3753
[48] Bayesian sensitivity models for missing covariates in the analysis of survival data
Hemming, Karla
Hutton, Jane Luise
JOURNAL OF EVALUATION IN CLINICAL PRACTICE, 2012, 18 (02) : 238 - 246
[49] Dynamic survival analysis for non-Markovian epidemic models
Di Lauro, Francesco
KhudaBukhsh, Wasiur R.
Kiss, Istvan Z.
Kenah, Eben
Jensen, Max
Rempala, Grzegorz A.
JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2022, 19 (191)
[50] Multivariate survival analysis models for incident duration with censored data
Jiang, Hong
Fang, Shouen
Chen, Yuren
Tongji Daxue Xuebao/Journal of Tongji University, 2012, 40 (12): : 1808 - 1813

← 1 2 3 4 5 →