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Journal of Computational and Graphical Statistics Volume 23, 2014 - Issue 4
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ARTICLES: Regression and Variable Selection

Variable Selection in General Frailty Models Using Penalized H-Likelihood

Il Do Ha
,
Jianxin Pan
,
Seungyoung Oh
&
Youngjo Lee
Pages 1044-1060 | Received 01 Mar 2013, Published online: 20 Oct 2014

Citations (17)

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Read on this site (1)

Sookhee Kwon, Il Do Ha & Jong-Min Kim. (2020) Penalized variable selection in copula survival models for clustered time-to-event data. Journal of Statistical Computation and Simulation 90:4, pages 657-675.
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Articles from other publishers (16)

Liangyuan Hu. (2023) A new method for clustered survival data: Estimation of treatment effect heterogeneity and variable selection. Biometrical Journal.
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Fatima-Zahra Jaouimaa, Il Do Ha & Kevin Burke. (2023) Penalized variable selection in multi-parameter regression survival modeling. Statistical Methods in Medical Research 32:12, pages 2455-2471.
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Xifen Huang, Jinfeng Xu & Yunpeng Zhou. (2022) Efficient algorithms for survival data with multiple outcomes using the frailty model. Statistical Methods in Medical Research 32:1, pages 118-132.
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Trias W. Rakhmawati, Il Do Ha, Hangbin Lee & Youngjo Lee. (2021) Penalized variable selection for cause‐specific hazard frailty models with clustered competing‐risks data. Statistics in Medicine 40:29, pages 6541-6557.
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Il Do Ha & Youngjo Lee. (2021) A review of h-likelihood for survival analysis. Japanese Journal of Statistics and Data Science 4:2, pages 1157-1178.
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Woojoo Lee, Il Do Ha, Maengseok Noh, Donghwan Lee & Youngjo Lee. (2021) A review on recent advances and applications of h-likelihood method. Journal of the Korean Statistical Society 50:3, pages 681-702.
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Wagner Barreto-Souza & Vinícius Diniz Mayrink. (2018) Semiparametric generalized exponential frailty model for clustered survival data. Annals of the Institute of Statistical Mathematics 71:3, pages 679-701.
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Eunyoung Park, Sookhee Kwon, Jihoon Kwon, Richard Sylvester & Il Do Ha. (2019) Penalized h‐likelihood approach for variable selection in AFT random‐effect models. Statistica Neerlandica.
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Eunyoung Park & Il Do Ha. (2018) Penalized variable selection for accelerated failure time models with random effects. Statistics in Medicine 38:5, pages 878-892.
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David D. HanagalDavid D. Hanagal. 2019. Modeling Survival Data Using Frailty Models. Modeling Survival Data Using Frailty Models 123 134 .
Eunyoung Park & Il Do Ha. (2018) Penalized variable selection for accelerated failure time models. Communications for Statistical Applications and Methods 25:6, pages 591-604.
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Bohyeon Kim, Il Do Ha & Donghwan Lee. (2016) Analysis of multi-center bladder cancer survival data using variable-selection method of multi-level frailty models. Journal of the Korean Data and Information Science Society 27:2, pages 499-510.
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Il Do Ha & Geon-Ho Cho. (2015) Variable selection in Poisson HGLMs using h-likelihoood. Journal of the Korean Data and Information Science Society 26:6, pages 1513-1521.
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Bohyeon Kim, Il Do Ha, Maengseok Noh, Myung Hwan Na, Ho-Chun Song & Jahae Kim. (2015) Variable Selection in Frailty Models using FrailtyHL R Package: Breast Cancer Survival Data. Korean Journal of Applied Statistics 28:5, pages 965-976.
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Il Do Ha, Maengseok Noh, Youngjo Lee, Johan Lim, Jaeyong Lee, Heeseok Oh, Dongwan Shin, Sanggoo Lee, Jinuk Seo, Yonhtae Park, Sungzoon Cho, Jonghun Park, Youkyung Kim & Kyungsang You. (2015) Survival Analysis using SRC-Stat Statistical Package. Korean Journal of Applied Statistics 28:2, pages 309-324.
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Youngjo Lee. (2015) Review of Mixed-Effect Models. Korean Journal of Applied Statistics 28:2, pages 123-136.
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