Transformation works for non-normality? On one-sample transformation trimmed t methods

Wei-Ming Luh, Jiin Huarng Guo

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

If the assumption of normality is not satisfied, there is no simple solution to this problem for the one-sample t test. The present study proposes Hall's or Johnson's transformation in conjunction with the trimmed mean to deal with the problem. Computer simulation is carried out to evaluate the small-sample behaviour of the proposed methods in terms of Type I error rate and statistical power. The proposed methods are compared with the conventional Student t, Yuen's trimmed t, Johnson's transformation untrimmed t, and Hall's transformation untrimmed t statistics for one-sided and two-sided tests. The simulation results indicate that the proposed methods can control Type I error well in very extreme conditions and are more powerful than the conventional methods.

Original languageEnglish
Pages (from-to)227-236
Number of pages10
JournalBritish Journal of Mathematical and Statistical Psychology
Volume54
Issue number2
DOIs
Publication statusPublished - 2001 Jan 1

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Arts and Humanities (miscellaneous)
  • Psychology(all)

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