Regression analysis of bivariate current status data under the Gamma-frailty proportional hazards model using the EM algorithm

Current Status Data ◽

Current Status ◽

Gamma Frailty ◽

Hazards Model ◽

The Em Algorithm ◽

Regression analysis of bivariate current status data under the proportional hazards model

Canadian Journal of Statistics ◽

10.1002/cjs.11344 ◽

2017 ◽

Vol 45 (4) ◽

pp. 410-424 ◽

Cited By ~ 5

Author(s):

Tao Hu ◽

Qingning Zhou ◽

Jianguo Sun

Keyword(s):

Regression Analysis ◽

Proportional Hazards ◽

Current Status Data ◽

Current Status ◽

Hazards Model ◽

New statistical software for the proportional hazards model with current status data

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2008.02.007 ◽

2008 ◽

Vol 52 (9) ◽

pp. 4272-4286 ◽

Cited By ~ 6

Author(s):

Solange Mongoué-Tchokoté ◽

Jong-Sung Kim

Keyword(s):

Proportional Hazards ◽

Current Status Data ◽

Current Status ◽

Statistical Software ◽

Hazards Model ◽

Bayesian proportional hazards model for current status data with monotone splines

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2011.03.013 ◽

2011 ◽

Vol 55 (9) ◽

pp. 2644-2651 ◽

Cited By ~ 24

Author(s):

Bo Cai ◽

Xiaoyan Lin ◽

Lianming Wang

Keyword(s):

Proportional Hazards ◽

Current Status Data ◽

Current Status ◽

Monotone Splines ◽

Hazards Model ◽

Efficient estimation for the proportional hazards model with competing risks and current status data

Canadian Journal of Statistics ◽

10.1002/cjs.10033 ◽

2009 ◽

Vol 37 (4) ◽

pp. 592-606 ◽

Cited By ~ 10

Author(s):

Jianguo Sun ◽

Junshan Shen

Keyword(s):

Competing Risks ◽

Proportional Hazards ◽

Efficient Estimation ◽

Current Status Data ◽

Current Status ◽

Hazards Model ◽

Partially linear single-index proportional hazards model with current status data

Journal of Multivariate Analysis ◽

10.1016/j.jmva.2016.06.004 ◽

2016 ◽

Vol 151 ◽

pp. 14-36 ◽

Cited By ~ 2

Author(s):

Xuewen Lu ◽

Pooneh Pordeli ◽

Murray D. Burke ◽

Peter X.-K. Song

Keyword(s):

Proportional Hazards ◽

Current Status Data ◽

Current Status ◽

Single Index ◽

Partially Linear ◽

Hazards Model ◽

Efficient estimation of a varying-coefficient partially linear proportional hazards model with current status data

Journal of Statistical Computation and Simulation ◽

10.1080/00949655.2019.1673391 ◽

2019 ◽

Vol 90 (1) ◽

pp. 90-111

Author(s):

Jun-Qiang Yang ◽

Yuan Dong ◽

Radhey Singh ◽

Cheng Dong ◽

Xuewen Lu

Keyword(s):

Proportional Hazards ◽

Efficient Estimation ◽

Current Status Data ◽

Current Status ◽

Varying Coefficient ◽

Partially Linear ◽

Hazards Model ◽

A partially linear proportional hazards model for current status data

Biometrics ◽

10.1111/biom.12914 ◽

2018 ◽

Vol 74 (4) ◽

pp. 1240-1249 ◽

Cited By ~ 1

Author(s):

Minggen Lu ◽

Christopher S. McMahan

Keyword(s):

Proportional Hazards ◽

Current Status Data ◽

Current Status ◽

Partially Linear ◽

Hazards Model ◽

Regression analysis for current status data using the EM algorithm

Statistics in Medicine ◽

10.1002/sim.5863 ◽

2013 ◽

Vol 32 (25) ◽

pp. 4452-4466 ◽

Cited By ~ 26

Author(s):

Christopher S. McMahan ◽

Lianming Wang ◽

Joshua M. Tebbs

Keyword(s):

Regression Analysis ◽

Em Algorithm ◽

Current Status Data ◽

Current Status ◽

The Em Algorithm ◽

Efficient estimation for the proportional hazards model with bivariate current status data

Lifetime Data Analysis ◽

10.1007/s10985-007-9058-9 ◽

2007 ◽

Vol 14 (2) ◽

pp. 134-153 ◽

Cited By ~ 19

Author(s):

Lianming Wang ◽

Jianguo Sun ◽

Xingwei Tong

Keyword(s):

Proportional Hazards ◽

Efficient Estimation ◽

Current Status Data ◽

Current Status ◽

Hazards Model ◽

A simulation‐extrapolation approach for regression analysis of misclassified current status data with the additive hazards model

Statistics in Medicine ◽

10.1002/sim.9184 ◽

2021 ◽

Author(s):

Shuwei Li ◽

Tian Tian ◽

Tao Hu ◽

Jianguo Sun

Keyword(s):

Regression Analysis ◽

Current Status Data ◽

Current Status ◽

Additive Hazards Model ◽

Additive Hazards ◽

Hazards Model ◽

Simulation Extrapolation ◽