Spatial extended hazard model with application to prostate cancer survival-Reference-Cited by-同舟云学术

Spatial extended hazard model with application to prostate cancer survival

Published:2014-12-17 Issue:2 Volume:71 Page:313-322
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biom

Author:

Li Li¹,Hanson Timothy²,Zhang Jiajia³

Affiliation:

1. Department of Mathematics and Statistics; University of New Mexico; Albuquerque, New Mexico U.S.A.

2. Department of Statistics; University of South Carolina; Columbia, South Carolina U.S.A.

3. Department of Epidemiology and Biostatistics; University of South Carolina; Columbia, South Carolina U.S.A.

Funder

Institut national de la santé et de la recherche médicale

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/biom.12268/fullpdf

Reference37 articles.

1. Frailty modeling for spatially correlated survival data, with application to infant mortality in Minnesota;Banerjee;Biostatistics,2003

2. Bayesian image restoration, with two applications in spatial statistics;Besag;Annals of the Institute of Statistical Mathematics,1991

3. Hyper-g priors for generalized linear models;Bové;Bayesian Analysis,2011

4. Linear regression with censored data;Buckley;Biometrika,1979

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Extended excess hazard models for spatially dependent survival data;Statistical Methods in Medical Research;2024-03-06

2. On near‐redundancy and identifiability of parametric hazard regression models under censoring;Biometrical Journal;2023-07-02

3. Mixed-Effects Parametric Proportional Hazard Model with Generalized Log-Logistic Baseline Distribution;Journal of Data Analysis and Information Processing;2023

4. Amoud Class for Hazard-Based and Odds-Based Regression Models: Application to Oncology Studies;Axioms;2022-11-01

5. Bayesian and Frequentist Approaches for a Tractable Parametric General Class of Hazard-Based Regression Models: An Application to Oncology Data;Mathematics;2022-10-15