Using Johnson's transformation and robust estimators with heteroscedastic test statistics: An examination of the effects of non-normality and heterogeneity in the non-orthogonal two-way ANOVA design

Luh Wei-Ming, Guo Jiin-Huarng

研究成果: Article同行評審

11 引文 斯高帕斯(Scopus)

摘要

The present study proposes a procedure that combines Johnson's transformation and the trimmed means method to deal with the problem of non-normality. An approximate test such as the Alexander-Govern test or Welch-James type test is then employed to deal with the heterogeneity of cell variance in the non-orthogonal two-way fixed effects completely randomized design. Both unweighted and weighted means analyses are considered. The empirical Type I error rates and the statistical power for comparing population means are investigated by Monte Carlo simulation. The simulated results show that Johnson's transformation with trimmed mean and the approximate test is valid in terms of Type I error rate control, and that the magnitude of the statistical power for non-normal distributions is better than that of conventional methods.

原文English
頁(從 - 到)79-94
頁數16
期刊British Journal of Mathematical and Statistical Psychology
54
發行號1
DOIs
出版狀態Published - 2001 5月

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 藝術與人文(雜項)
  • 一般心理學

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