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Testing methods for the one-way fixed effects ANOVA models of log-normal samples

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  • Jiin-Huarng Guo
  • Wei-Ming Luh

Abstract

For one-way fixed effects of log-normal data with unequal variance, the present study proposes a method to deal with heterogeneity. An appropriate hypothesis testing is demonstrated; and one of the approximate tests, such as the Alexander-Govern test, Welch test or James second-order test, is applied to control Type I error rate. Monte Carlo simulation is used to investigate the performance of the F test for log-scale, the F test for original scale, the James second-order test, the Welch test, and the Alexander-Govern test. The simulated results and real data analysis show that the proposed method is valid and powerful.

Suggested Citation

  • Jiin-Huarng Guo & Wei-Ming Luh, 2000. "Testing methods for the one-way fixed effects ANOVA models of log-normal samples," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 731-738.
    • Handle: RePEc:taf:japsta:v:27:y:2000:i:6:p:731-738
    DOI: 10.1080/02664760050081915
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    Cited by:

    1. Li, Xinmin, 2009. "A generalized p-value approach for comparing the means of several log-normal populations," Statistics & Probability Letters, Elsevier, vol. 79(11), pages 1404-1408, June.
    2. Ayanendranath Basu & Abhijit Mandal & Nirian Martín & Leandro Pardo, 2019. "A Robust Wald-Type Test for Testing the Equality of Two Means from Log-Normal Samples," Methodology and Computing in Applied Probability, Springer, vol. 21(1), pages 85-107, March.

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