TY - JOUR
T1 - Transformation works for non-normality? On one-sample transformation trimmed t methods
AU - Luh, Wei-Ming
AU - Guo, Jiin Huarng
PY - 2001/1/1
Y1 - 2001/1/1
N2 - 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.
AB - 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.
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U2 - 10.1348/000711001159537
DO - 10.1348/000711001159537
M3 - Article
C2 - 11817091
AN - SCOPUS:0035514359
VL - 54
SP - 227
EP - 236
JO - British Journal of Statistical Psychology
JF - British Journal of Statistical Psychology
SN - 0007-1102
IS - 2
ER -