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Emeritus Faculty

Youngjo Lee Emeritus professor

MajorHierarchial generalized linear model
Office25-216
Emailyoungjo@snu.ac.kr
RESEARCH AREAS
Generalized Linear Model, Hierarchical Generalized Linear Model, Data Science, Statistical Software Development
DEGREES
1979
B.S. Seoul National University
1981, 1983
M.S. & Ph.D. Iowa State University
BIOGRAPHY
1983-1985
Assistant Professor, Oregon State University

1985-1986

Assistant Professor, Oklahoma State University
1986-1990,
1990-1994
Assistant Professor and Associate Professor, Hallym University
1994-1999,
1999-present
Associate Professor and Professor, Seoul National University
1996-Present
Fellow of Royal Statistical Society
1996-Present
Members of International Statistical Institute (
2004-Present
Professor, Seoul National University College of Medicine
2005-2007
President of Korea Data Mining Society
2006~2013
Director of research team for Statistical Analysis of Bio, Financial & Industrial Data(Brain Korea 21)
2011-Present
Director of Data Science and knowledge Creation research center
2013-Present
Karolinska Institute Adjunct Professor
2013-Present
Fellow of the Korean academy of science and technology
2013-Present
Fellow of the American Statistical Association
SELECTED PUBLICATIONS
Lee, Y., Nelder, J. A. and Pawitan, Y. (2006). Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood. London: Chapman and Hall.
Lee, Y., Nelder, J. A. and Pawitan, Y. (2017). Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood(2nd edition). London: Chapman and Hall.
Lee, Y., Rönnegård, L. and Noh, M. (2017). Data analysis using Hierarchical Generalized Linear Models with R.
Ha, I., Jeoug, J. and Lee, Y. (2017). Statistical modelling of survival data with random effects: H-likelihood approach. New York: Springer.
Choi, D., Jang, D., Lai, T., Lee, Y., Lu, Y., Ni, J., Qian, P., Qiu, P. and Tiao, G. (2018) Proceedingsof the Pacific Rim Statistical Conference forProduction Engineering: Big Data, Production Engineering and Statistics. Springer Nature Singapore Pte Ltd.
Ng, T., Lee, W. and Lee, Y. (2018). Change-point estimators with true identification property. Bernoulli Journal, 24(1), 616-660.
Noh, M., Jin, S. and Lee, Y. (2018). H-likelihood approach to factor analysis for ordinal data. Structural equation modelling: A Multidisciplinary Journal, 25(4), 530-540.
Ji, S. et al. (2018) The dialkyl resorcinol stemphol disrupts calcium homeostasis to trigger programmed immunogenic necrosis in cancer. Cancer Letters, 416, 109-123.
Lee, T., Noh, M. and Ha, I. (2018). The Real-Time Tracking and Alarming the Early Neurological Deterioration Using Continuous Blood Pressure Monitoring in Patient with Acute Ischemic Stroke. Edited by Choi,D et al.
Lee, S., Lee, Y. and Pawitan, Y. (2018). Sparse pathway-based prediction models for high-throughput molecular data. Computational Statistics and Data analysis, 126, 125-135 Kim, Y., Jang, H., Lee, Y., Lee, D. and Kim, D. (2018). Effects of Internet and smartphone addiction on depression and anxiety based on propensity score matching analysis. International Journal of Environmental Research and Public Health, 15(5), 859.
Noh, M. and Lee, Y. (2018). Extended negative binomial hurdle models. To appear in Statistical Methods in Medical Research.
Xu, P., Shi, J. and Lee, Y. (2018). Automatic Detection of Significant Areas for Functional Data with Directional Error Control. To appear in Statistics in Medicine.
Mazumder, A. et al. (2018) Hydroxycoumarin OT-55 kills CML cells alone or in synergy with Imatinib or Synribo: involvement of ER stress and DAMP release. To appear in Cancer Letters
Pawitan, Y. and Lee, Y. (2017). Wallet game: probability, likelihood and extended likelihood. American Statistician, 71(2), 120-122.
Wang, Z, Shi, J. Q. and Lee Y. (2017). Extended T-process Regression Models. Journal of Statistical Planning and Inference, 189, 38-60.
Kim, J., Park, S. and Lee, Y. (2017). Statistical inference using generalized linear mixed models under informative cluster sampling. Canadian Journal of Statistics, 45(4), 479-497.
Das, RN., Lee, Y. and Mukhopadhya, BB. (2017). The Basal, Peak and Maximum Heart Rate Determinants of the Cardiac Patients Who Underwent Dobutamine Stress Echocardiography. Mathews Journal of Cardiology, 2(2):013.
Park, S., Shin, W., Park, Y. and Lee, Y. (2017). Building a new culture for quality management in the era of the 4th industrial revolution. Total Quality Management & Business Excellence, 28(9), 934-945.
Ha, I., Noh, M. and Lee, Y. (2017). H-likelihood Approach for Joint Modelling of Longitudinal Outcomes and Time to Event data. Biometrical Journal, 59(6), 1122-1143.
Ning, Z., Lee, Y., Joshi, PK., Wilson, JF., Pawitan, Y. and Shen, X. (2017). A selection operator for summary association statistics reveals allelic heterogeneity of complex traits. The American Journal of Human Genetics, 101(6), 903-912.
Lim, J., Noh, M., Kim, B., Han, M., Kims, S., Jang, M., Lee, Y., Ha, I., Yu, K., Lee, B., Kang, Y., Lee, J. and Bae, H. (2017). A methodological perspective for the longitudinal cognitive change after stroke. Dementia and Geriatric Cognitive Disorders, 44(5-6), 311-319.
Kim, W., Zeng, P., Shi, J., Lee, Y. and Paik, N. (2017) Semi-automatic Tracking, Smoothing and Segmentation of Hyoid Bone Motion from Videofluoroscopic Swallowing Study. PLOS ONE, 12(11): e0188684
Chung, I., Oh, J., Lee, S., Jang, I., Lee, Y. and Chung, J. (2017) A post hoc analysis of intra-subject coefficients of variation optimal sample sizes for bioequivalence studies. Translational and Clinical Pharmacology, 25(4), 179-182.
Lee, S., Pawitan, Y., Ingelsson, E. and Lee, Y. (2017). Sparse estimation of gene–gene interactions in prediction models. Statistical Methods in Medical Research, 26(5), 2319-2332.
Cao, C., Shi, JQ. and Lee, Y. (2017). Robust functional regression model for marginal mean and subject-specific inferences. To appear in Statistical Methods in Medical Research.
Lee, Y., Molas, M. and Noh, M. (2017). mdhglm: A Package for Fitting Multivariate Double Hierarchical Generalized Linear Models with H-likelihood. To appear in R Journal.
Noh, M. and Lee, Y. (2017). Joint random-effect models for mean and dispersion via the R package dhglm. To appear in the Journal of Statistical Software.
Kim, K. and Lee, Y. (2017). Marginal versus conditional beta-binomial regression models. To appear in Statistical Methods in Medical Research
Chung, I., Oh, J., Lee, S., Jang, I., Lee, Y. and Chung, J. (2017) A post hoc analysis of intra-subject coefficients of variation optimal sample sizes for bioequivalence studies. Translational and Clinical Pharmacology, 25(4), 179-182.
Ha, I., Christian, N., Jeong, J., Park, J. and Lee, Y. (2016). Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties. Statistical Methods in Medical Research, 25(6), 2488-2505.
Sarpong, S. A., Nsowah-Nuamah, N. N. N., Avuglah, R. K., Oh, S. and Lee, Y. (2016). Performance assessment of Penalized variable selection methods using crop yield data from the three Northern Regions of Ghana. International Journal of Probability and Statistics, 5(1), 10-17.
Lee, Y., Alam, M., Noh, M., Rönnegård, L. and Skarin, A. (2016). Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts. Ecology and Evolution, 6, 7047-7056.
Ng, T., Oh, S. and Lee, Y. (2016). Going beyond oracle property: Selection consistency and uniqueness of local solution of the generalized linear model. Statistical Methodology, 32, 147-160.
Choi, K., Tak, J., Lee, D., Kim, S. and Lee, Y. (2016). Survey on addiction and mental health status of the homeless. The Korean Journal of Applied Statistics, 29(5), 977-985.
Lee, D. and Lee, Y. (2016). Extended likelihood approach to multiple testing with directional error control under a hidden Markov random field model. Journal of Multivariate Analysis, 151, 1-13.
Park, J., Choi, S., Choi, B., Lee, C., Kim, H., Kim, Y., Park, K., Lee, Y., Kang, S., Lim, K. and Chung, J. (2016). Arsenic levels in the groundwater of Korea and the urinary excretion among contaminated area. Journal of Exposure Science & Environmental Epidemiology, 26, 458-463.
Kwon, S., Oh, S. and Lee, Y. (2016). The use of random-effect models for high-dimensional variable selection problems. Computational Statistics and Data Analysis, 103, 401-412.
Kim, J., Han, M. and Lee, Y. and Park, Y. (2016). Futuristic data-driven scenario building : Incorporating text mining and fuzzy association rule mining into fuzzy cognitive map. Expert Systems with Applications, 57, 311-323.
Lee, Y. and Kim, G. (2016). H-Likelihood Predictive Intervals for Unobservables. International Statistical Review, 84(3), 487-505.
Sarpong, S., Oh, S., Avuglah, R. Nsowah-Nuamah, N. and Lee, Y. (2015). Analysis of Crop Yield Physical Support Services Data Using Hierarchical Generalized Linear Models. International Journal of Statistics and Applications, 5(5), 196-207.
Kang, D., Song, B., Yoon, B., Lee, Y. and Park, Y. (2015). Diffusion pattern analysis for social networking sites using small-world network multiple influence model. Technological Forecasting & Social Change, 95, 73-86.
Lee, S., Pawitan, Y. and Lee, Y. (2015). A random-effect model approach for group variable selection. Computational Statistics and Data Analysis, 89, 147–157.
Paik, C.M., Lee, Y. and Ha, I. (2015). Frequentist Inference on Random Effects Based on Summarizability, Statistica Sininca, 25, 1107-1132.
Das, R., Kim, J. and Lee, Y. (2015). Robust First Order Rotatable Lifetime Improvement Experimental Designs. Journal of Applied Statistics, 42(9), 1911-1930.
Geum, Y., Lee, H., Lee, Y. and Park, Y. (2015). Development of data-driven technology roadmap considering dependency: An ARM-based technology roadmapping. Technological Forecasting and Social Change, 91, 264-279.
Lee, D., Kang, H., Kim, E., Lee, H., Kim, H., Kim, Y., Lee, Y. and Lee, D. (2015). Optimal likelihood-ratio multiple testing with application to Alzheimer’s disease and questionable dementia. BMC Medical Research Methodology, 15(9).
Lee, W., Kim, J., Lee, Y., Park, T., and Suh, Y. (2015). A Hierarchical Generalized Linear Model in Combination with Dispersion Modeling to Improve Sib-Pair Linkage Analysis. Human Heredity, 80(1), 12-20.
홍은희, 이영조, 옥유진, 나명환, 노맹석, 하일도 (2015). Analysis of field test data using robust linear mixed-effect model. The Korean Journal of Applied Statistics, 28(2), 361-369.
이영조 (2015). Review of mixed effect models. The Korean Journal of Applied Statistics, 28(2), 123-136.
최규빈, 오희석, 이영조, 김동호, 유경상 (2015). Variational mode decomposition with missing data. The Korean Journal of Applied Statistics, 28(2), 175-188.
안형미, 이영조, 유경상 (2015). Bio-equivalence analysis using linear mixed model. The Korean Journal of Applied Statistics, 28, 2.
노맹석, 하일도, 이영조, 임요한, 이재용, 오희석, 신동완, 이상구, 서진욱, 박용태, 조성준, 박종현, 김유경, 유경상 (2015). SRC-Stat package for fitting double hierarchical generalized linear models. The Korean Journal of Applied Statistics, 28(2), 343-351.
하일도, 노맹석, 이영조, 임요한, 이재용, 오희석, 신동완, 이상구, 서진욱, 박용태, 조성준, 박종현, 김유경, 유경상 (2015). Survival analysis using SRC-Stat statistical package. The Korean Journal of Applied Statistics, 28(2), 309-324.
Yi, S., An, H., Lee, H., Lee, S., Ieiri, I. and Lee, Y. (2014). Korean, Japanese, and Chinese populations featured similar genes encoding drug-metabolizing enzymes and transporters: a DMET Plus microarray assessment. Pharmacogenetics and Genomics, 24(10), 477-485.
Ha, I., Pan, J., Oh, S. and Lee, Y. (2014). Variable Selection in General Frailty Models using Penalized H-likelihood. Journal of Computational and Graphical Statistics, 23(4), 1044-1060,
Lee, M., Ha, I. and Lee, Y. (2014). Frailty modeling for clustered competing risks data with missing cause of failure. Statistical Methods in Medical Research.
Ha, I., Lee, M., Oh, S., Jeong, J., Sylvester, R. and Lee, Y. (2014). Variable selection in subdistribution hazard frailty models with competing risks data. Statistics in Medicine, 33, 4590-4604
Ha, I., Christian, N., Jeong, J., Park, J. and Lee, Y. (2014). Frailty modeling for clustered competing risks data with missing cause of failure. Statistical Methods In Medical Research.
Ha, I., Pan, J., Oh, S. and Lee, Y. (2014). Variable selection in general frailty models using penalized h-likelihood. Journal of Computational and Graphical Statistics, 23(4), 1044-1060.
Lee, Y. and Oh, H. (2014). A new sparse variable selection via random-effect model. Journal of Multivariate analysis, 125, 89-99.
Yoon, E., Kim, Y., Kim, H., Kim, S., Lee, Y. and Shin, H. (2014). Transcranial Direct Current Stimulation to Lessen Neuropathic Pain After Spinal Cord Injury A Mechanistic PET Study. Neurorehabilitation&Neural Repair, 28, 250-259.
Kang, J., Bae, H., Noh, M., Kim, W., Lee, Y., and Han, M. (2014). Real-Time Prediction of Early Neurologic Deterioration Using Continuous Blood Pressure Embedded Model in Ischemic Stroke. Cerebrovascular Diseases, 38, 100-100.
Yoon, E., Kim, Y., Shin, H. Lee, Y. and Kim, S. (2013). Cortical and white matter alterations in patients with neuropathic pain after spinal cord injury. Brain Research, 1540, 64-73.
Ronnegard, L. and Lee, Y. (2013). Exploring the potential of Hierarchical Generalized Linear Models in animal breeding and genetics. Journal of animal breeding and genetics, 6, 415-416.
Lee, Y. and Ha, I. (2013). Hierarchical Likelihood and Statistical Inferences. Quantitative Bio-Science, 32, 81-88.
Lee, W. and Lee, Y. (2013). Random-effect models with singular precision. Journal of Statistical Planning and Inference, 12, 2128-2141.
Kim, J., Kim, K., Kim, M., Cho, C., Lee, Y. and Lee, J. (2013). Statistical Multisite Simulations of Summertime Precipitation over South Korea and Its Future Change Based on Observational data. Asia-Pacific Journal of Atmospheric Sciences , 49, 687-702.
Noh, M., Lee, Y., Chu, C. Gwack, J. Youn, S. and Huh, S. (2013). Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?. Osong Public Health and Research Perspectives, 4, 39-44.
Felleki, M., Lee, D., Lee, Y. and Glimour, A. (2013). Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models. Genetics Research, 94, 307-317.
Ha, I., Vaida, F. and Lee, Y. (2013). Interval estimation of random effects in proportional hazards model with frailties. Statistical Methods in Medical Research.
Lee, Y. and Bjornstad, J. (2013). Extended likelihood approach to large-scale multiple testing. Journal of the Royal Statistical Society: Series B(Statistical Methodology), 75, 553-575.
Lee, Y. and Noh, M. (2012). Modeling random effect variance with double hierarchical generalized linear models. Statistical Modelling, 12, 487-502.
Lee, D., Lee, Y., Paik, C.M. and Kenward, M. (2012). Robust Inference Using Hierarchical Likelihood Approach for Heavy-tailed Longitudinal Outcomes with Missing Data: an Alternative to Inverse Probability Weighted Generalized Estimating Equations. Computational Statistics and Data Analysis, 59, 171-179.
Alam, M., Noh, M. and Lee, Y. (2012). Likelihood estimate of treatment effects under selection bias. Statistics and Its Interface, 6, 349-359.
Ha, I., Noh, M. and Lee, Y. (2012). frailtyHL: A Package for Fitting Frailty Models with H-likelihood. The R journal, 4(2), 28-37.
Noh, M., Wu, L. and Lee, Y. (2012). Hierarchical likelihood methods for nonlinear and generalized linear mixed models with missing data and measurement errors in covariates. Journal of Multivariate Analysis, 109, 42-51.
Lee, W. and Lee, Y. (2012). Modifications of REML algorithm for HGLMs, Statistics and Computing. 22, 959-966.
Noh, M., Lee, Y., Oh, S., Cheun, H., Cho, S., Lee, W., Chu, C., and Huh, S. (2012). Spatial and temporal distribution of Plasmodium vivax malaria in Korea estimated with a hierarchical generalized linear model, Osong Public Health and Research Perspectives, 3, 192-198.
이동환, 이재용, 오희석, 이영조 (2012). 시공간 상관성을 고려한 일기산출기 모형을 이용한 4대강 유역별 미래 일기 변수 산출. 응용통계연구, 25, 351-362. Felleki, M., Lee, D., Lee, Y., Glimour, A. and Ronnegard, L. (2012). Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models. Genetics Research, 94(6), 307-317.
Review of “A note on the properties of the reproductive dispersion model by Tian and Yuebao”, MathSciNet Mathematical Reviews MR2669779 (2011k:62215)
Sparse partial least-squares regression and its applications to high-throughput data analysis, Chemometrics and Intelligent Laboratory Systems, 109(1), 1-8 (with Lee, D)
Sparse Canonical Covariance Analysis for High-throughput Data, Statistical Applications in Genetics and Molecular Biology, 10(1), Article 30 (with Lee)
Robust Estimation of Dropout Models using hierarchical likelihood , Journal of Statistical Computation and Simulation, 81(6), 693-706 (with Noh, M. and Kenward, M.)
HGLMs for Quality Improvement, Applied Stochastic Models in Business and Industry, 27(3), 315-328 (with Park, H.J. and Nelder, J.A.)
Collective Intelligence Ratio: Measurement of Intellectual Behaviors in Real-time Multimodal Interactions for Technology Innovation Design Projects, Team Performance Management, 17, 41-62 (with Kim, P.)
The hierarchical-likelihood approach to autoregressive stochastic volatility models, Computational Statistics and Data Analysis, 55, 248-260(with Lee, W)
Orthodox BLUP versus h-likelihood methods for inferences about random effects in Tweedie mixed models, Statistics and Computing, 20, 295-303. (with Ha, I.)
Approximate conditional inference in mixed-effects models with binary data, Computational Statistics and Data Bias reduction of likelihood estimators in semiparametric frailty models, Scandinavian Journal of Statistics, 37, 307-320 (with Ha, I. and Noh, M.)
Bias reduction of likelihood estimators in semiparametric frailty models, Scandinavian Journal of Statistics, 37, 307-320 (with Ha, I. and Noh, M.)
Analysis strategies for multiple responses in quality improvement experiments, International Journal of Quality Engineering and Technology, 1, 395-409 (with R. N. Das)
Super-sparse principal component analyses for high-throughput genomic data, BMC Bioinformatics 2010, 11:296 (with Lee, D)
Prediction interval for disease mapping using hierarchical likelihood, Computational Statistics, 26, 159-179 (with Jang, M and Lee, W.)
Improved multisite stochastic weather generation with applications to historical data in South Korea, Asia-Pacific Journal of Atmospheric Sciences, 46, 497-504 (with Lee, D)
Log-normal versus gamma models for analyzing data from quality-improvement experiments , Quality Engineering, Vol 21, Number 1, 2009, Pages 79-87 (with Das, Rabindra)
On weighting of bivariate margins in pairwise likelihood, Journal of Multivariate Analysis, Vol 100, Issue 4, April 2009, Pages 670-685 (with Joe,H.)
Log-normal versus gamma models for analyzing data from quality-improvement experiments , Quality Engineering, Vol 21, Number 1, 2009, Pages 79-87 (with Das, Rabindra)
Discussion of Rue et al’s paper , J. R. Statist. Soc. B, 71, Issue 2, pp.373
Log-normal versus gamma models for analyzing data from quality-improvement experiments , Quality Engineering, Vol 21, Number 1, 2009, Pages 79-87 (with Das, Rabindra)
Rejoinder, Statistical Science, 24, 294-302 (with Nelder, J.A.)
GLM-methods for volatility models , Statistical Modelling, Vol 8, pp.263-283 (with Castillo, J.)
Hierarchical-likelihood approach for nonlinear mixed-effects models, Computational Statistics and Data Analysis.Vol 52, pp.3517-3527 (with Noh, M.)
“Improving resistivity of urea formaldehyde resin through joint modeling of mean and dispersion”, Quality Engneering, Vol 20, Issue 3, pp 287 – 295 (with Das, Rabindra)
Discussion of McCullagh’s paper , J. R. Statist. Soc. B, 70,Part 4, pp.672
A fast wavelet approach for recovering damaged images, Journal of Applied Statistics, 35(8), 927-938. (with D. Kim and H. Oh)
REML estimation for binary data in GLMMs, J. of Multivariate Analysis, Vol 98, pp896-915 (with Noh,M.)
H-likelihood:problems and solutions”, Statistics and Computing, Vol 17, pp49-55 (with Nelder, J.A., Noh M.)
Robust modelling for inference from GLM classes, JASA, Vol 102, pp.1059-1072, (with Noh, M.)
Genetic mixed linear models for twin survival data. Behavior Genetics, vol 37, pp621-630, (with Ha, I. and Pawitan, Y.)
Model selection for multi-component frailty models. Statistics in Medicine , Vol 26, 4790-4807, (with Ha, I. and MacKenzie, G.)
Using Hierarchical Likelihood for Missing Data Problems. Biometrika, Vol 94, pp.905-919, (with Yun, S. and Kenward, M.)
“Discussion of Zeng & Lin’s paper”, J. R. Statist. Soc. B, 69, pp.552
“A comparison of the Hierarchical likelihood and Bayesian approaches to spatial epidemiological modelling”, Environmetrics , Vol 18, Issue 7, pp.809-821 (with Jang. M )
Review of “Linear and Generalized Linear Mixed Models and Their Applications by Jiming Jiang”, Biometrics, Vol 63, pp.1297-1298
Review of “Linear and Generalized Linear Mixed Models and Their Applications by Jiming Jiang”, Biometrics, Vol 63, pp.1297-1298
“Double hierarchical generalized linear model”(with discussion), J.R.Statist.Soc.C, 55, pp 139-180, (with Nelder)
Rejoinder, J.R.Statist.Soc.C. 55, pp 180-185, (with Nelder)
“Fitting via alternative random-effect models”,Statistics and Computing. Vol.16 ,pp 69-75,(with Nelder)
“Modelling and estimating heavy-tailed non-homogeneous correlated queues pareto-inverse gamma HGLMs with covariates”, J. of Applied Statistics, Vol. 33, No. 4, pp 417-425, (with Yun, S. and Sohn, S.Y)
Review of “Linear and Generalized Linear Mixed Models and Their Applications by Jiming Jiang”, Biometrics, Vol 63, pp.1297-1298
Review of “Linear and Generalized Linear Mixed Models and Their Applications by Jiming Jiang”, Biometrics, Vol 63, pp.1297-1298
Review of “Linear and Generalized Linear Mixed Models and Their Applications by Jiming Jiang”, Biometrics, Vol 63, pp.1297-1298
Hierarchical likelihood-based wavelet method for denoising signals with missing data. IEEE Signal Processing Letters, Vol 13, pp.361-364 (with Kim,D. and Oh, H.S.)
Determinants of Hospital Closure in South Korea : Use of a Hierarchical Generalized Linear Model(HGLM), Social Science & Medicine Vol 63, pp 2320-2329, (with Noh)
“HGLM versus conditional estimators for the analysis of clustered binary data”, Statistics in medicine, Vol. 24, pp 741-752,(with Kang W, Lee M)
“Multilevel Mixed Linear Models for Survival Data”, Life time data analysis, Vol. 11, pp 131-142, (with Ha,I.)
    “HGLM versus conditional estimators for the analysis of clustered binary data”, Statistics in medicine, Vol. 24, pp 741-752,(with Kang W, Lee M)

 

    “HGLM versus conditional estimators for the analysis of clustered binary data”, Statistics in medicine, Vol. 24, pp 741-752,(with Kang W, Lee M)
“Comparison of hierarchical likelihood versus orthodox BLUP approach for frailty models”, Biometrika, Vol. 92, pp 717-723,(with Ha I.)
“Likelihood for random-effects models”(with discussion), Statistics and Operations Research Transactions, Vol.29, pp 141-178,(With Nelder, J.A.)
“Likelihood for random-effects models”(with discussion), Statistics and Operations Research Transactions, Vol.29, pp 141-178,(With Nelder, J.A.)
“Conditional and marginal models: another view”(with discussion), Statistical Science, Vol. 19, pp 219-233, (with Nelder)
“Rejoinder”, Statistical Science, Vol. 19, pp 234-238,(with Nelder)
“Comparison of Hierarchical and Marginal Likelihood Estimators for Binary Outcomes”, Computational Statistics and Data Analysis, Vol. 45, pp639-650.(with Yun, S.)
“Estimating intraclass correlation for binary data using extended quasi-likelihood “, Statistical Modelling, Vol. 4, pp113-126
“Estimating intraclass correlation for binary data using extended quasi-likelihood “, Statistical Modelling, Vol. 4, pp113-126
“Robust Design via generalized linear models”, Journal of the Quality Technology, Vol. 35, N0. 1, pp2-12 (with Nelder, J. A.)
“Biases of the restricted maximum likelihood estimators for ARMA processes with polynomial time trend”, Journal of Statistical Planning and Inference, Vol. 116, pp163-176 (with Kang, W., Shin, D.W.)
“Unweighted mean squares for the general two variance component mixed models”, Proceedings for Graybill Conference, Corolado State University Press, pp281-299(with Eubank, L., Seely, J.)
“False parsimony and its detection with GLMs”, Journal of Applied Statistics, Vol. 30, pp477-483(with Nelder, J. A.)
“Estimating fraility models via Poission hierarchical generalized linear models”, Journal of Computational and Graphical Statistics, Vol. 12, pp663-681(with Ha, I. D.)
“Joint modelling of repeated measures and survival time data”, Biometrical Journal, Vol 45, pp647-658 (with Ha,I.D., Park,T.S.)
“Extended REML estimators”, Journal of Applied Statistics, Vol.30, pp845-856 (with Nelder, J. A.)
“Robust Design via generalized linear models”, Journal of the Quality Technology, Vol. 35, N0. 1, pp2-12 (with Nelder, J. A.)
“시계열에서의 국면전환 예측 모형의 개발”, 선물연구 제11권 제1호,pp57-98(with 류근관,빈기범,조성준)
“Analyzing Weather Effects on Airborne Particulate Matter with HGLM”, Environmetrics, Vol 14, pp687-697 (with Yun. S. and Lee, Y)
“Analysis of the ulcer data using hierarchical generalized linear models” Statistics in Medicine,21,pp191-202 (with Nelder,J.A.)
“Robust variance estimators for fixed-effect estimates with hierarchical- likelihood”, Statistics and Computing, 12, pp201-207
“Hierarchical likelihood approach for mixed linear models with censored data “, Life time data analysis, 8, pp163-176 (with Ha,I. et al.)
“Discussion of Spiegelhater et al’s paper “, J.R.Statist.Soc.B, 64, pp632
“무응답이 있는 설문조사연구의 접근법 : 한국노인약물역학 코호트 자료의 평가”, 예방의학회지 제 35권 제 2호, pp136-140 (with Jieun Back, Wichang Kang and Byungju Park)
“Fixed-effect versus random-effect models for evaluating therapeutic preferences”, Statistics in medicine, 21, pp2325-2330
“Procedures HGANALYSE, HGDISPLAY, HGFIXEDMODELS, HGKEEP, HGPLOT and HGRANDOMMODEL.” In Genstat Release 6.1 Reference manual, Part 3 Procedure Library PL14(ED. R. W. Payne & G. M. Arnold), pp.243-252. Oxford: VSN International. (with Nelder,J.A. and Payne, R.W.)
“Procedures HGANALYSE, HGDISPLAY, HGFIXEDMODELS, HGKEEP, HGPLOT and HGRANDOMMODEL.” In Genstat Release 6.1 Reference manual, Part 3 Procedure Library PL14(ED. R. W. Payne & G. M. Arnold), pp.243-252. Oxford: VSN International. (with Nelder,J.A. and Payne, R.W.)
“Hierarchical likelihood approach for frailty models”, Biometrika, 88, pp.233-243 (with Ha,I. and Song,J.-K.)
“Modelling and analysing correlated non-normal data”, Statistical Modelling, 1, pp.7-16 (with Nelder,J.A.)
“Hierarchical likelihood approach for frailty models”, Biometrika, 88, pp.233-243 (with Ha,I. and Song,J.-K.)
“Hierarchical likelihood approach for frailty models”, Biometrika, 88, pp.233-243 (with Ha,I. and Song,J.-K.)
“The relationship between double exponential families and extended quasi-likelihood families “, Applied Statistics, 49, pp.413-419 (with Nelder,J.A.)
“Two ways of modelling overdispersion in non-normal data “, Applied Statistics, 49, part 4, pp.591-598 (with Nelder,J.A.)
“HGLMs for analysis of correlated non-normal data “, Compstat, edited by Bethlehem,J.G. and van der Heijden,P.G.M., Physica-Verlag, pp.97-107 (with Nelder,J.A.)
“GLMs with random effects “, Invited Talk, International Biometric Society, July 3-7, San Francisco USA (with Nelder,J.A.)
“Application of Mathematical Modeling to Extraplate from High Dose to Low Dose for Risk Assessment of Vinyl Chloride”, Journal of Food Hygiene and Safety, Vol.15, No.3, pp.267-270 (with Lee,S and Jung,J)
“Fitting host-parasitoid models with CV2>1 using hierarchical generalized linear models “, Proc. R. Soc. Lond. B. 267, pp.2043-2048 (with Perry,J. et al.)
“평균과 분산의 동시모형에 따른 회귀진단법에 관한 연구 “, 응용통계연구, 13, pp.407-414 (with Kang,W. et al.)
“디피리다몰 부하 심근관류 SPECT의 장기예후 예측능”, 대한핵의학회지 제34권 제1호, pp.39-54 (with Lee,D. and Jang,M. et. al.)
“비연속변수를 종속변수로 하는 비교 임상시험시 통계적 검정력 산출”, Kor.J.Clin.Pharmacol.Ther., Vol.8, No.2, (with Kwak,M et al.)
“The robustness of the quasi-likelihood estimator”, The Canadian Journal of Statistics, 27, 2, pp.321-327, (with Nelder, J.A.)
“Joint Modelling of the Mean and Dispersion for the analysis of quality-improvement experiments”, Statistical Process Monitoring and Optimization, edited by Park and Vining, Chapter 23, pp.387-394, (with Nelder, J.A.)
“Population-adjusted mean age at incidence (PAMA) for comparing incidence partterns with age in different populations “, Korean Journal of Epidemiology, 21, pp.31-35, (with Ahn, Y. et al.
“Mixed Linear Models with Censored Data “, Journal of Korean Statistical Society, 28, pp.211-233, (with Ha, I. et al.)
“Estimating Methods on Exponential Regression Models “, Journal of Korean Statistical Society, 28, pp.195-210, (with Ha, I. et al.)
Analysis of Grouped Duration Data with “Hierarchical Generalized Linear Models “, Compstat, edited by Payne, R. and Lane, P, Prism Digital Colour Ltd. pp.197-198 (with Noh, M. and Ryu, K.)
“Extended REML using GLM Technology : a New Formulation “, TR, Imperial College, (with Nelder, J.A.)
“일부 K-DRG 환례의 의료기관 유형별 수술 및 처치진료비의 변이분석 모형”, 보건행정학 회지, 8(1), pp.1-14, (with Maengseok Noh et al.)
“밭의 비옥도를 고려한 품종실험 분석”, The Korean Journal of Applied Statistics, 11(2) pp.423-433, (with Seongchul Yun et al.)
“Generalized linear models for the analysis of quality-improvement experiments”, The Canadian Journal of Statistics, 26, pp.95-105, (with Nelder J.A.)
“Joint modeling of mean and dispersion”, Technometrics, 40, pp.168-175, (with Nelder J.A.)
“Sire evaluation of count traits with a Poisson-Gamma hierarchical generalized linear model”, Asian-Australasian Journal of Animal Sciences, 11, pp.642-647, (with Lee, C.)
“위암 위험요인에 대한 코호트 연구의 방법론적 고찰: 추적조사 불완전성을 중심으로”, 한국역학회지, 19(2), pp.152-160, (with Moosong Lee et al.)
“로그선형모형을 이용한 복수 평가자들간의 신뢰도 연구”, 대한예방의학회지, 3(4), pp. 719-728, (with Sungim Lee et al.)
“일반적인 SN비에 관한 소고”, Journal of the Korean Society for Quality Management, 25(4), pp.48-98, (with Yongbin Lim)
“Characterizing sums of squares by their distributions”, American Statistician, 51, pp.55-58, (with Seely,J. and Birkes,D.)
“Extended quasi-likelihood and estimating equations approach”, IMS Notes- monograph series, edited by Basawa, Godambe and Tayler, pp.139-148 (with Nelder, J.A.)
“Hierarchical Generalized Linear Models”(with discussion). J.R.Statist.Soc.B, 58(4), pp.619-673, (with J.A.Nelder)
“Computing the Wald Interval for a Variance Ratio”, Biometrics, 52, pp.1486-1491, (with Justus Seely)
“Recovery of inter-block information:extensions in a two variance component model”, Communication in Statistics:Theory and Method, 25, pp.2189-2200,(with Saleh A. and Seely,J.)
“일반화선형모형을 통한 품질개선실험 자료분석”, Journal of the Korean Society for Quality Management, 24(2), pp.128-141, (with Yongbin Lim)
“의대생의 전문직 사회화 과정에 대한 고찰”, 대한예방의학회지, 29(2), pp.265-278, (with Dalsun Han et al.)
“Rejoinder of the paper by Lee and Nelder”, J.R.Statist.Soc.B, 58(4), pp.673-678, (with Nelder,J.A.)
“Rejoinder of the paper by Lee and Nelder”, J.R.Statist.Soc.B, 58(4), pp.673-678, (with Nelder,J.A.)
“Rejoinder of the paper by Lee and Nelder”, J.R.Statist.Soc.B, 58(4), pp.673-678, (with Nelder,J.A.)
Lee, Y. and Birkes, D. (1994). Shrinking toward submodels in regression. Journal of Statistical Planning and Inference, 41, 95-111.
Lee, Y. and Seely, J. (1994). A Note on the Satterthwaite Confidence Interval for a Variance. Communication in Statistics: Theory and Method, 23(3), 859-869.
Lee, Y. and Bae, S. (1994). 고혈압환자의 치료순응도에 영향을 미치는 요인. 보건행정학회지, 4, 25-48.
Lee, Y. and Koo, JY. (1994). Bivariate B-Splines in generalized linear models. Journal of Statistical Computing and Simulation, 50, 119-129.
AWARDS

2017

Sudang Prize in basic sciences
2017
Korean Scientific Reward in field of mathematics
2014
2014 SNU Research Award
2012
BK21 award in field of essential and basic technology of science by Minister of Education, Science and Technology
2017
Best research award of College of Natural Sciences, Seoul National University
2008
The winner of 2008 Gallup Korea Award
2008
Achievement award of Korea Data Mining Society
SOFTWARES
ALBATROSS ANALYTICS
Youngjo Lee, Marek Molas and Maengseok Noh (2016). mdhglm: Multivariate Double Hierarchical Generalized Linear Models. R package version 1.6. https://CRAN.R-project.org/package=mdhglm
Youngjo Lee and Maengseok Noh (2016). dhglm: Double Hierarchical Generalized Linear Models. R package version 1.6. https://CRAN.R-project.org/package=dhglm
Il Do HA, Maengseok Noh and Youngjo Lee (2012). frailtyHL: Frailty Models via H-likelihood. R package version 1.1. https://CRAN.R-project.org/package=frailtyHL