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A new generalized p-value for testing equality of inverse Gaussian means under heterogeneity

Author

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  • Shi, Jian-Hong
  • Lv, Jiang-Long

Abstract

For the problem of comparing the means of k inverse Gaussian (IG) populations, a new generalized pivot quantity is defined and the generalized p-value based on this generalized pivot quantity is also given. Numerical results indicate that the proposed test has excellent type I error control for both balanced and unbalanced cases, and tends to be robust for the number of populations, whereas the type I error probability of the Tian’s generalized test can be much larger than the nominal level for a bigger value of k. The proposed procedure is illustrated using two examples.

Suggested Citation

  • Shi, Jian-Hong & Lv, Jiang-Long, 2012. "A new generalized p-value for testing equality of inverse Gaussian means under heterogeneity," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 96-102.
    • Handle: RePEc:eee:stapro:v:82:y:2012:i:1:p:96-102
    DOI: 10.1016/j.spl.2011.08.022
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    References listed on IDEAS

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    1. Ye, Ren-Dao & Ma, Tie-Feng & Wang, Song-Gui, 2010. "Inferences on the common mean of several inverse Gaussian populations," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 906-915, April.
    2. Tian, Lili, 2006. "Testing equality of inverse Gaussian means under heterogeneity, based on generalized test variable," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1156-1162, November.
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    Cited by:

    1. Liu, Xuhua & Li, Na & Hu, Yuqin, 2015. "Combining inferences on the common mean of several inverse Gaussian distributions based on confidence distribution," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 136-142.

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