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Normalized Johnson's transformation one-sample trimmed t for non-normality

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  • Jiin-Huarng Guo
  • Wei-Ming Luh

Abstract

The present study suggests the use of the normalized Johnson transformation trimmed t statistic in the one-sample case when the assumption of normality is violated. The performance of the proposed method was evaluated by Monte Carlo simulation, and was compared with the conventional Student t statistic, the trimmed t statistic and the normalized Johnson's transformation untrimmed t statistic respectively. The simulated results indicate that the proposed method can control type I error very well and that its power is greater than the other competitors for various conditions of non-normality. The method can be easily computer programmed and provides an alternative for the conventional t test.

Suggested Citation

  • Jiin-Huarng Guo & Wei-Ming Luh, 2000. "Normalized Johnson's transformation one-sample trimmed t for non-normality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(2), pages 197-203.
    • Handle: RePEc:taf:japsta:v:27:y:2000:i:2:p:197-203
    DOI: 10.1080/02664760021736
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