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

Jiin Huarng Guo, Wei Ming Luh

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)197-203
Number of pages7
JournalJournal of Applied Statistics
Volume27
Issue number2
DOIs
Publication statusPublished - 2000 Jan 1

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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