Min–max crossover designs for two treatments binary and poisson crossover trials

被引：0
作者：
Satya Prakash Singh
Siuli Mukhopadhyay
Harsh Raj
机构：
[1] Indian Institute of Technology Hyderabad,Department of Mathematics
[2] Indian Institute of Technology Bombay,Department of Mathematics
来源：
Statistics and Computing | 2021年 / 31卷
关键词：
Correlated responses; Crossover trials; Generalized estimating equation; Min–max design;
D O I：
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学科分类号：
摘要：
In this article min–max crossover designs for binary and Poisson crossover trials with two treatments are proposed. Models with and without carryover effects are considered. Min–max designs for periods 2 and 3 are discussed in details. A sensitivity analysis is performed to assess the robustness of proposed designs when compared to existing optimal designs. An equivalence theorem is provided to verify optimality of min–max designs.
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  • [1] Bandyopadhya U(2009)Adaptive two-treatment two-period crossover design for binary treatment responses incorporating carry-over effects Stat. Methods Appl. 18 13-33
  • [2] Biswas A(2000)Crossover designs for two-treatment clinical trials J. Stat. Plan. Inference 87 125-134
  • [3] Mukherjee S(2007)Maximin and Bayesian optimal designs for regression models Stat. Sin. 17 463-480
  • [4] Carriere KC(1992)A Bayesian approach to the analysis of binary crossover data J. R. Stat. Soc. Ser. D 43 13-29
  • [5] Huang R(2017)Influence diagnostics for count data under AB-BA crossover trials Stat. Methods Med. Res. 26 2938-2950
  • [6] Dette H(2006)The R package geepack for generalized estimating equations J. Stat. Softw. 15 1-11
  • [7] Haines LM(2001)Maximin designs for exponential growth models and heteroscedastic polynomial models Ann. Stat. 29 561-576
  • [8] Imhof LA(1981)Two-treatment crossover designs for estimating a variety of effects J. Am. Stat. Assoc. 76 612-619
  • [9] Forster J(1997)Optimal repeated measurements designs: the linear optimality equations Ann. Stat. 25 2328-2344
  • [10] Hao C(1998)Optimal and efficient repeated measurements designs for uncorrelated observations J. Am. Stat. Assoc. 93 1176-1187
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