title: Proper metrics for clinical trials: transformations and other procedures to remove non-normality effects.
abstract: 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.
authors.affiliation: FDA/CBER/Office of Biostatistics and Epidemiology, 1401 Rockville Pike, HFM-215, Rockville, MD 20852, USA. lachenbruch@cber.fda.gov
authors.forename: Peter A
authors.initials: PA
authors.lastname: Lachenbruch
mesh_terms: D000818:Animals; D019187:Cadmium Compounds / Q000506:poisoning; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D006259:Craniocerebral Trauma; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D010087:Oxides / Q000506:poisoning; D015203:Reproducibility of Results; D014481:United States
chemical_list: D019187:Cadmium Compounds; D010087:Oxides; C029663:cadmium oxide