Choice of optimal second stage designs in two-stage experiments

被引:0
|
作者
A. M. Elsawah
机构
[1] Zagazig University,Department of Mathematics, Faculty of Science
[2] BNU-HKBU United International College,Division of Science and Technology
来源
Computational Statistics | 2018年 / 33卷
关键词
Second stage design; Second stage map; Two-stage design; Uniform design; Optimal design; Complementary design;
D O I
暂无
中图分类号
学科分类号
摘要
In real-life projects, in order to obtain precious information about the process, we often partition the experiment into two stages with equal size. The main purpose of this article is to study how to choose the first stage experimental designs (FSED) and the second stage experimental designs (SSED) to construct uniform or at least good approximation to uniform (GATU) two-stage experimental designs (TSED) that involve a mixture of ω1≥1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\omega _1\ge 1$$\end{document} factors with μ1≥2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu _1\ge 2$$\end{document} levels and ω2≥1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\omega _2\ge 1$$\end{document} factors with μ2≥2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu _2\ge 2$$\end{document} levels whether regular or nonregular. Through theoretical justification, this paper proves that the SSED is uniform (GATU) if and only if the FSED is uniform (GATU), the TSED is uniform (GATU) if and only if its corresponding complementary TSED is uniform (GATU), and the TSED is uniform or at least GATU if and only if the FSED is uniform.
引用
收藏
页码:933 / 965
页数:32
相关论文
共 50 条
  • [1] Choice of optimal second stage designs in two-stage experiments
    Elsawah, A. M.
    COMPUTATIONAL STATISTICS, 2018, 33 (02) : 933 - 965
  • [2] Optimal two-stage designs for binary response experiments
    Sitter, RR
    Forbes, BE
    STATISTICA SINICA, 1997, 7 (04) : 941 - 955
  • [3] Optimal designs for two-stage inference
    Stallrich, Jonathan
    McKibben, Michael
    JOURNAL OF QUALITY TECHNOLOGY, 2024, 56 (04) : 327 - 341
  • [4] A variational approach to optimal two-stage designs
    Pilz, Maximilian
    Kunzmann, Kevin
    Herrmann, Carolin
    Rauch, Geraldine
    Kieser, Meinhard
    STATISTICS IN MEDICINE, 2019, 38 (21) : 4159 - 4171
  • [5] Optimal planning of adaptive two-stage designs
    Pilz, Maximilian
    Kunzmann, Kevin
    Herrmann, Carolin
    Rauch, Geraldine
    Kieser, Meinhard
    STATISTICS IN MEDICINE, 2021, 40 (13) : 3196 - 3213
  • [6] Two-stage designs for experiments with a large number of hypotheses
    Zehetmayer, S
    Bauer, P
    Posch, M
    BIOINFORMATICS, 2005, 21 (19) : 3771 - 3777
  • [7] Optimal two-stage group-sequential designs
    Lokhnygina, Yuliya
    Tsiatis, Anastasios A.
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2008, 138 (02) : 489 - 499
  • [8] Optimal two-stage designs for exploratory basket trials
    Zhou, Heng
    Liu, Fang
    Wu, Cai
    Rubin, Eric H.
    Giranda, Vincent L.
    Chen, Cong
    CONTEMPORARY CLINICAL TRIALS, 2019, 85
  • [9] Practical considerations for optimal two-stage designs with binary outcomes
    Ho, SY
    Yao, RJ
    AMERICAN STATISTICAL ASSOCIATION - 1996 PROCEEDINGS OF THE BIOPHARMACEUTICAL SECTION, 1996, : 108 - 111
  • [10] Optimal sample size division in two-stage seamless designs
    Berry, Lindsay R.
    Marion, Joe
    Berry, Scott M.
    Viele, Kert
    PHARMACEUTICAL STATISTICS, 2024,