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

Jiin-Huarng Guo and Wei-Ming Luh

Journal of Applied Statistics, 2000, vol. 27, issue 2, 197-203

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.

Date: 2000
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DOI: 10.1080/02664760021736

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