scholarly journals Multiple imputation of missing covariates for the Cox proportional hazards cure model

2016 ◽  
Vol 35 (26) ◽  
pp. 4701-4717 ◽  
Author(s):  
Lauren J. Beesley ◽  
Jonathan W. Bartlett ◽  
Gregory T. Wolf ◽  
Jeremy M. G. Taylor
Keyword(s):  
Multiple Imputation ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Missing Covariates ◽  
Cure Model

scholarly journals Estimation in a Cox Proportional Hazards Cure Model

Biometrics ◽  
2000 ◽  
Vol 56 (1) ◽  
pp. 227-236 ◽  
Author(s):  
Judy P. Sy ◽  
Jeremy M. G. Taylor
Keyword(s):  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Cure Model

Assessing the prediction accuracy of cure in the Cox proportional hazards cure model: an application to breast cancer data

2014 ◽  
Vol 13 (6) ◽  
pp. 357-363 ◽  
Author(s):  
Junichi Asano ◽  
Akihiro Hirakawa ◽  
Chikuma Hamada
Keyword(s):  
Breast Cancer ◽  
Prediction Accuracy ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Breast Cancer Data ◽  
Cure Model ◽  
Cancer Data

scholarly journals Bayesian random threshold estimation in a Cox proportional hazards cure model

2013 ◽  
Vol 33 (4) ◽  
pp. 650-661 ◽  
Author(s):  
Lili Zhao ◽  
Dai Feng ◽  
Emily L. Bellile ◽  
Jeremy M. G. Taylor
Keyword(s):  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Threshold Estimation ◽  
Cure Model ◽  
Random Threshold

Change point detection in Cox proportional hazards mixture cure model

2020 ◽  
pp. 096228022095911
Author(s):  
Bing Wang ◽  
Jialiang Li ◽  
Xiaoguang Wang
Keyword(s):  
Survival Data ◽  
Change Point ◽  
Proportional Hazards ◽  
Test Procedure ◽  
Cox Proportional Hazards ◽  
Change Point Detection ◽  
Parameter Estimates ◽  
Finite Sample ◽  
Cure Model ◽  
Mixture Cure Model

The mixture cure model has been widely applied to survival data in which a fraction of the observations never experience the event of interest, despite long-term follow-up. In this paper, we study the Cox proportional hazards mixture cure model where the covariate effects on the distribution of uncured subjects’ failure time may jump when a covariate exceeds a change point. The nonparametric maximum likelihood estimation is used to obtain the semiparametric estimates. We employ a two-step computational procedure involving the Expectation-Maximization algorithm to implement the estimation. The consistency, convergence rate and asymptotic distributions of the estimators are carefully established under technical conditions and we show that the change point estimator is n consistency. The m out of n bootstrap and the Louis algorithm are used to obtain the standard errors of the estimated change point and other regression parameter estimates, respectively. We also contribute a test procedure to check the existence of the change point. The finite sample performance of the proposed method is demonstrated via simulation studies and real data examples.

scholarly journals Standard errors for the cox proportional hazards cure model

2001 ◽  
Vol 33 (12-13) ◽  
pp. 1237-1251 ◽  
Author(s):  
J.P. Sy ◽  
J.M.G. Taylor
Keyword(s):  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Standard Errors ◽  
Cure Model

scholarly journals Extension of a Cox proportional hazards cure model when cure information is partially known

Biostatistics ◽  
2014 ◽  
Vol 15 (3) ◽  
pp. 540-554 ◽  
Author(s):  
Y. Wu ◽  
Y. Lin ◽  
S.-E. Lu ◽  
C.-S. Li ◽  
W. J. Shih
Keyword(s):  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Cure Model

scholarly journals Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation

2014 ◽  
Vol 33 (27) ◽  
pp. 4681-4694 ◽  
Author(s):  
Dan Jackson ◽  
Ian R. White ◽  
Shaun Seaman ◽  
Hannah Evans ◽  
Kathy Baisley ◽  
...  
Keyword(s):  
Multiple Imputation ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Independent Censoring
Sign in / Sign up

Export Citation Format

Share Document