Penalized estimation in parametric frailty model

被引：0
|
作者：
Ahelali, Marwan H. [1 ]
Alamri, Osama Abdulaziz [2 ]
Sirohi, Anu [3 ]
机构：
[1] Univ Tabuk, Dept Stat, Tabuk 71491, Saudi Arabia
[2] Univ Tabuk, Dept Stat, Tabuk 71491, Saudi Arabia
[3] Amity Univ, Dept Stat, AIAS, Noida, India
来源：
HELIYON | 2024年 / 10卷 / 16期
关键词：
Frailty model; Collinearity; Ridge estimator; Principal component estimator; Infant mortality; RELIABILITY ESTIMATION; LOGISTIC-REGRESSION; RIDGE REGRESSION; COLLINEARITY; SURVIVAL;
D O I：
10.1016/j.heliyon.2024.e35848
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Frailty model examines the effect of observable and non-observable factors on time to event data. Presence of collinearity produces unstable estimates of parameters. Therefore, this research focus on the penalized estimation of frailty model and proposed the new estimator which is the extension of ridge and principal component estimators. Simulation is run to reveal the performance of proposed estimator. Moreover, the technique is applied on NFHS (National Family Health Survey) data to examine the infant mortality in India.
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页数：9
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