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Statistics in Biopharmaceutical Research Volume 12, 2020 - Issue 3: 2020 Special Issue on Vaccines and Biologics
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Original Articles

Hierarchical Linear Models for Multiregional Clinical Trials

Saemina KimDepartment of Applied Statistics, Yonsei University, Seoul, KoreaView further author information
&
Seung-Ho KangDepartment of Applied Statistics, Yonsei University, Seoul, KoreaCorrespondence[email protected]
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Pages 334-343 | Received 20 Sep 2018, Accepted 24 Jul 2019, Published online: 16 Sep 2019

Citations (5)

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Read on this site (3)

Chunkyun Park & Seung-Ho Kang. (2023) Random intercept hierarchical linear model for multi-regional clinical trials. Journal of Biopharmaceutical Statistics 0:0, pages 1-21.
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Junhui Park & Seung-Ho Kang. (2022) Hierarchical Generalized Linear Models for Multiregional Clinical Trials. Statistics in Biopharmaceutical Research 14:3, pages 358-367.
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Makoto Aoki, Hisashi Noma & Masahiko Gosho. (2021) Methods for detecting outlying regions and influence diagnosis in multi-regional clinical trials. Biostatistics & Epidemiology 5:1, pages 30-48.
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Articles from other publishers (2)

Xin Liu, Rong‐Xian Yue & Weng Kee Wong. (2022) Equivalence theorems for c and DA‐optimality for linear mixed effects models with applications to multitreatment group assignments in health care. Scandinavian Journal of Statistics 49:4, pages 1842-1859.
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Xin Liu, Min Ye & Rong-Xian Yue. (2021) Optimal designs for comparing population curves in hierarchical models. Statistics & Probability Letters 178, pages 109192.
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