From "Manga Guide to Statistics", Shin Takahashi, 2008
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Eun Jeong Min
Eun Jeong Min
Contacts
Contacts
Mailing Address:
Department of Medical Life Sciences,
College of Medicine, The Catholic University of Korea
222 Banpo daero, Seocho-gu, Seoul, 06591, South Korea
E mail: ej.min@catholic.ac.kr
Phone: +822-3147-8413
Master Students
Master Students
함석호
함석호
Missing Data Imputation / Survival Clustering Analysis
email: hahm.seokho@gmail.com
손예진
손예진
Survival Analysis for Competing Risk Data
email: sohn.yejin.9@gmail.com
김민서
김민서
TBD
email: minseo.kim251@gmail.com
최원서
최원서
PS estimation and Weighting for multil-level data with unmeasured cluster confoudings (Rcode)
email: 1seo.choi00@gmail.com
이재훈
이재훈
TBD
email: jhjr96@gmail.com
심세원
심세원
Bayesian Clustering
email: sewonshim@gmail.com
Graduates (MS)
Graduates (MS)
정시성
정시성
2023. Aug
Jeong, Siseong, and Eun Jeong Min. "A simulation study for various propensity score weighting methods in clinical problematic situations." The Korean Journal of Applied Statistics 36.5 (2023): 381-397.
current: inno.N
박은경
박은경
2024. Aug
Park, E., and Min, E.J., "Adaptive Continual Reassessment Method: A MTD estimation method in phase I clinical trial", The Korean Journal of Applied Statistics, 37(4), 411-444.
current: 한국오츠카제약
박근호
박근호
2025. Feb
Park, K., and Min, E.J., “Comparative study of deep learning methods for survival outcomes: applications to SEER data”, The Korean Journal of Applied Statistics, 38(1):45-62.
current: 알엔비에스
이승수
이승수
2024. Feb
Lee, Seungsoo, and Eun Jeong Min. "A comparison study of canonical methods: Application to-Omics data." The Korean Journal of Applied Statistics 37.2: 157-176.
current: CRScube
유하린
유하린
2025. Feb
Yoo, H., and Min, E.J., “Accuracy and Safety of Dose-escalation Designs for Phase I Oncology Trials Considering Delayed Toxicity”, The Korean Journal of Applied Statistics, 38(2):119-168.
current: CNR research
팽소연
팽소연
2025. Feb
Paeng, S., and Min, E.J., “Co-Inertia analysis for multi-omics data with FDR control via SLOPE”, Communications for Statistical Applications and Methods, 32(1), 91-106..
current: CC&I research
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