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The generalized inference on the sign testing problem about the normal variances

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  • Wei-Ya Wu
  • Wei-Hwa Wu
  • Hsin-Neng Hsieh
  • Meng-Chih Lee

Abstract

For the sign testing problem about the normal variances, we develop the heuristic testing procedure based on the concept of generalized test variable and generalized p-value. A detailed simulation study is conducted to empirically investigate the performance of the proposed method. Through the simulation study, especially in small sample sizes, the proposed test not only adequately controls empirical size at the nominal level, but also uniformly more powerful than likelihood ratio test, Gutmann's test, Li and Sinha's test and Liu and Chan's test, showing that the proposed method can be recommended in practice. The proposed method is illustrated with the published data.

Suggested Citation

  • Wei-Ya Wu & Wei-Hwa Wu & Hsin-Neng Hsieh & Meng-Chih Lee, 2018. "The generalized inference on the sign testing problem about the normal variances," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(5), pages 956-970, April.
    • Handle: RePEc:taf:japsta:v:45:y:2018:i:5:p:956-970
    DOI: 10.1080/02664763.2017.1325857
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    Cited by:

    1. Hsin-Neng Hsieh & Hung-Yi Lu, 2020. "The generalized inference on the ratio of mean differences for fraction retention noninferiority hypothesis," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-12, June.

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