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A new two-stage multiple comparison procedure for comparing several exponential populations with a control under heteroscedasticity

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  • Maurya, Vishal
  • Gill, A.N.
  • Goyal, Aarti

Abstract

A new two-stage multiple comparison procedure, which maintains power at a pre-specified level, is proposed to construct simultaneous confidence intervals (SCIs) for the distances of location parameters of k treatments from the location of control under heteroscedasticity of scale parameters by taking k+1 members of two parameter exponential distributions. Simulation study reveals that the proposed two-stage procedure performs better than the existing two-stage procedure of Lam and Ng (1990) in terms of coverage probability and average volume of the simultaneous confidence intervals. No additional tables are required to implement the proposed procedure. Implementation of proposed procedure is demonstrated by taking real life data.

Suggested Citation

  • Maurya, Vishal & Gill, A.N. & Goyal, Aarti, 2017. "A new two-stage multiple comparison procedure for comparing several exponential populations with a control under heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 1-11.
    • Handle: RePEc:eee:csdana:v:108:y:2017:i:c:p:1-11
    DOI: 10.1016/j.csda.2016.10.021
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    References listed on IDEAS

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    1. Wu, Shu-Fei & Lin, Ying-Po & Yu, Yuh-Ru, 2010. "One-stage multiple comparisons with the control for exponential location parameters under heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1372-1380, May.
    2. Vishal Maurya & Amar Nath Gill & Parminder Singh, 2013. "Multiple comparisons with a control for exponential location parameters under heteroscedasticity," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1817-1830, August.
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    Cited by:

    1. Shu-Fei Wu, 2023. "Sample Size Determination for Two-Stage Multiple Comparisons for Exponential Location Parameters with the Average," Mathematics, MDPI, vol. 11(2), pages 1-11, January.

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