Multi‐subgroup gene screening using semi‐parametric hierarchical mixture models and the optimal discovery procedure: Application to a randomized clinical trial in multiple myeloma期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

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Multi‐subgroup gene screening using semi‐parametric hierarchical mixture models and the optimal discovery procedure: Application to a randomized clinical trial in multiple myeloma

Authors:	Shigeyuki Matsui Hisashi Noma Pingping Qu Yoshio Sakai Kota Matsui Christoph Heuck John Crowley

Institution:	1. Department of Biostatistics, Nagoya University Graduate School of Medicine, 65 Tsurumai‐cho, Showa‐ku, Nagoya, Aichi 466‐8550, Japan;2. Department of Data Science, The Institute of Statistical Mathematics, Tachikawa, Tokyo, Japan;3. Cancer Research And Biostatistics, Seattle, Washington, U.S.A.;4. Department of Gastroenterology, Kanazawa University Hospital, Kanazawa, Ishikawa, Japan;5. The Myeloma Institute, University of Arkansas for Medical Science, Little Rock, Arkansas, U.S.A.

Abstract:

Keywords:	Gene screening Multiple subgroups Optimal discovery procedure Prognostic and predictive genes Randomized clinical trials Semi‐parametric hierarchical mixture models