I. Ha

Most-cited papers

1. Hierarchical likelihood approach for frailty models

   I. Ha, Youngjo Lee, Jae-Kee Song

   2001120 citations

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2. Estimating Frailty Models via Poisson Hierarchical Generalized Linear Models

   I. Ha, Youngjo Lee

   200374 citations

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3. Statistical Modelling of Survival Data with Random Effects: H-Likelihood Approach

   I. Ha, Jong-Hyeon Jeong, Youngjo Lee

   201864 citations

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4. Frailty Modelling for Survival Data from Multi-Centre Clinical Trial

   I. Ha, R. Sylvester, C. Legrand, G. MacKenzie

   2011Statistics in Medicine55 citations Open access

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5. Model selection for multi‐component frailty models

   I. Ha, Youngjo Lee, G. MacKenzie

   2007Statistics in Medicine49 citations

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6. Deep Learning-Based Survival Analysis for High-Dimensional Survival Data

   Lin Hao, Juncheol Kim, Sook-Hee Kwon, I. Ha

   2021Mathematics44 citations Open access

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7. Comparison of hierarchical likelihood versus orthodox best linear unbiased predictor approaches for frailty models

   I. Ha, Youngjo Lee

   200543 citations

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8. Hierarchical-Likelihood Approach for Mixed Linear Models with Censored Data

   I. Ha, Youngjo Lee, Jae-Kee Song

   2002Lifetime Data Analysis43 citations

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9. frailtyHL: A Package for Fitting Frailty Models with H-likelihood

   I. Ha, M. Noh, Youngjo Lee

   2012The R Journal41 citations Open access

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10. Comparison of the marginal hazard model and the sub-distribution hazard model for competing risks under an assumed copula

    T. Emura, Jia-Han Shih, I. Ha, R. Wilke

    2019Statistical Methods in Medical Research39 citations Open access

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11. Variable Selection in General Frailty Models Using Penalized H-Likelihood

    I. Ha, Jianxin Pan, Seungyoung Oh, Youngjo Lee

    201429 citations

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12. Orthodox BLUP versus h-likelihood methods for inferences about random effects in Tweedie mixed models

    Youngjo Lee, I. Ha

    2010Statistics and computing26 citations

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13. Bias Reduction of Likelihood Estimators in Semiparametric Frailty Models

    I. Ha, M. Noh, Youngjo Lee

    201025 citations

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14. Deep learning-based residual control chart for count data

    Jong-Min Kim, I. Ha

    2022Quality Engineering20 citations

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15. Penalized variable selection for accelerated failure time models with random effects

    Eunyoung Park, I. Ha

    2019Statistics in Medicine20 citations

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16. Frailty modelling approaches for semi-competing risks data

    I. Ha, Li-Ming Xiang, Mengjiao Peng, Jong-Hyeon Jeong +1 more

    2019Lifetime Data Analysis18 citations

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17. Frequentist Inference on Random Effects Based on Summarizability

    M. Paik, Youngjo Lee, I. Ha

    201517 citations

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18. Frailty modeling for clustered competing risks data with missing cause of failure

    Minjung Lee, I. Ha, Youngjo Lee

    2017Statistical Methods in Medical Research16 citations

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19. Interval Estimation of Random Effects in Proportional Hazards Models with Frailties

    I. Ha, F. Vaida, Youngjo Lee

    2013Statistical Methods in Medical Research15 citations Open access

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20. Dispersion frailty models and HGLMs

    M. Noh, I. Ha, Youngjo Lee

    2006Statistics in Medicine15 citations

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21. Joint Modelling of Repeated Measures and Survival Time Data

    I. Ha, T. Park, Youngjo Lee

    200315 citations

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22. Profile likelihood approaches for semiparametric copula and frailty models for clustered survival data

    I. Ha, Jong-Min Kim, T. Emura

    2019Journal of Applied Statistics13 citations

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23. A review of h-likelihood for survival analysis

    I. Ha, Youngjo Lee

    2021Japanese Journal of Statistics and Data Science12 citations

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24. A Methodological Perspective on the Longitudinal Cognitive Change after Stroke

    Jae-Sung Lim, M. Noh, B. Kim, Moon-Ku Han +9 more

    2018Dementia and Geriatric Cognitive Disorders12 citations

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25. Flexible parametric copula modeling approaches for clustered survival data

    Sookhee Kwon, I. Ha, Jia-Han Shih, T. Emura

    2021Pharmaceutical statistics11 citations

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26. Penalized variable selection for accelerated failure time models

    Eunyoung Park, I. Ha

    2018Communications for Statistical Applications and Methods10 citations Open access

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27. H‐likelihood approach for joint modeling of longitudinal outcomes and time‐to‐event data

    I. Ha, M. Noh, Youngjo Lee

    2017Biometrical journal. Biometrische Zeitschrift10 citations

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28. Robust frailty modelling using non-proportional hazards models

    I. Ha, G. MacKenzie

    201010 citations Open access

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29. Frailty proportional mean residual life regression for clustered survival data: A hierarchical quasi‐likelihood method

    Rui Huang, Li-Ming Xiang, I. Ha

    2019Statistics in Medicine8 citations

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30. A visualizing method for investigating individual frailties using frailtyHL R-package

    I. Ha, M. Noh

    20138 citations Open access

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31. A study using HGLM on regional difference of the dead due to injuries

    Kil-Hun Kim, M. Noh, I. Ha

    20118 citations

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32. Genetic Mixed Linear Models for Twin Survival Data

    I. Ha, Youngjo Lee, Y. Pawitan

    2007Behavior Genetics8 citations

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33. H-likelihood approach for variable selection in gamma frailty models

    I. Ha, Geon-Ho Cho

    20127 citations

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34. Deep Learning-Based Residual Control Chart for Binary Response

    Jong-Min Kim, I. Ha

    2021Symmetry6 citations Open access

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35. Penalized variable selection for cause‐specific hazard frailty models with clustered competing‐risks data

    T. W. Rakhmawati, I. Ha, Hangbin Lee, Youngjo Lee

    2021Statistics in Medicine5 citations

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36. Penalized variable selection in copula survival models for clustered time-to-event data

    Sook-Hee Kwon, I. Ha, Jong-Min Kim

    20205 citations

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37. A HGLM framework for Meta-Analysis of Clinical Trials with Binary Outcomes

    I. Ha

    20085 citations

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38. Survival analysis for tomato big data in smart farming

    Jun Cheol Kim, Sookhee Kwon, I. Ha, M. Na

    20214 citations

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39. Variable selection in Poisson HGLMs using h-likelihoood

    I. Ha, Geon-Ho Cho

    20154 citations Open access

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40. Prediction of smart farm tomato harvest time: Comparison of machine learning and deep learning approaches

    Jihun Kim, Sookhee Kwon, I. Ha, M. Na

    2022Journal of the Korean Data and Information Science Society3 citations

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41. Application of Deep Learning and Neural Network to Speeding Ticket and Insurance Claim Count Data

    Jong-Min Kim, Jihun Kim, I. Ha

    2022Axioms3 citations Open access

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42. Special feature: Recent statistical methods for survival analysis

    T. Emura, I. Ha

    2021Japanese Journal of Statistics and Data Science3 citations Open access

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43. Penalized h‐likelihood approach for variable selection in AFT random‐effect models

    Eunyoung Park, Sook-Hee Kwon, J. Kwon, R. Sylvester +1 more

    2019Statistica neerlandica (Print)3 citations

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44. A correction of SE from penalized partial likelihood in frailty models

    I. Ha

    20093 citations

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45. Joint AFT random-effect modeling approach for clustered competing-risks data

    L. Hao, I. Ha, Jong-Hyeon Jeong, Youngjo Lee

    20242 citations Open access

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46. Subject-specific Deep Neural Networks for Count Data with High-cardinality Categorical Features

    Hangbin Lee, I. Ha, Chang-Soon Hwang, Youngjo Lee

    2023arXiv.org2 citations

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47. Machine learning techniques applied to US army and navy data

    J. M. Kim, Chuwen Li, I. Ha

    2019International Journal of Productivity and Quality Management2 citations

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48. Generalised linear mixed logit and probit models applied to US Army and Navy data

    J. M. Kim, Chuwen Li, I. Ha

    20192 citations

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49. Competing Risks Frailty Models

    I. Ha, Jong-Hyeon Jeong, Youngjo Lee

    20172 citations

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50. Maximum Likelihood Estimation Using Laplace Approximation in Poisson GLMMs

    I. Ha

    20092 citations

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