title: Transformation works for non-normality? On one-sample transformation trimmed t methods.
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.
authors.affiliation: Institute of Education, National Cheng Kung University, 1 University Road, Tainan, Taiwan 701, R. O. C. luhwei@mail.ncku.edu.tw
authors.forename: W M
authors.initials: WM
authors.lastname: Luh
authors.forename: J H
authors.initials: JH
authors.lastname: Guo
mesh_terms: D015982:Bias; D003198:Computer Simulation; D016001:Confidence Intervals; D006801:Humans; D015233:Models, Statistical; D016011:Normal Distribution