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Proper metrics for clinical trials: transformations and other procedures to remove non‐normality effects
Author(s) -
Lachenbruch Peter A.
Publication year - 2003
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1675
Subject(s) - normality , computer science , a priori and a posteriori , statistics , econometrics , data mining , mathematics , philosophy , epistemology
A simulation study was performed to study the effects of non‐normality and to examine procedures to ameliorate possible loss of power when data are incorrectly assumed to be normally distributed. It was found that only distributions with high asymmetry or heavy tails seriously affect the t‐test. The Box–Cox likelihood ratio test appears to have some advantages over the others, but this must be offset by the greater complexity in making the results understandable to non‐statisticians. The variability in outcomes with the different procedures demonstrates the importance of specifying such procedures a priori . Published in 2003 by John Wiley & Sons, Ltd.