title: Evaluating clinical significance: incorporating robust statistics with normative comparison tests.
abstract: The purpose of this study was to evaluate a modified test of equivalence for conducting normative comparisons when distribution shapes are non-normal and variances are unequal. A Monte Carlo study was used to compare the empirical Type I error rates and power of the proposed Schuirmann-Yuen test of equivalence, which utilizes trimmed means, with that of the previously recommended Schuirmann and Schuirmann-Welch tests of equivalence when the assumptions of normality and variance homogeneity are satisfied, as well as when they are not satisfied. The empirical Type I error rates of the Schuirmann-Yuen were much closer to the nominal α level than those of the Schuirmann or Schuirmann-Welch tests, and the power of the Schuirmann-Yuen was substantially greater than that of the Schuirmann or Schuirmann-Welch tests when distributions were skewed or outliers were present. The Schuirmann-Yuen test is recommended for assessing clinical significance with normative comparisons.
authors.affiliation: Department of Psychology, York University, Toronto, Canada.
authors.forename: Katrina
authors.initials: K
authors.lastname: van Wieringen
authors.forename: Robert A
authors.initials: RA
authors.lastname: Cribbie
mesh_terms: D001008:Anxiety Disorders / Q000523:psychology / Q000628:therapy*; D035843:Biomedical Research / Q000706:statistics & numerical data; D003866:Depressive Disorder / Q000523:psychology / Q000628:therapy*; D006801:Humans; D009010:Monte Carlo Method; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D011586:Psychology, Clinical / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000706:statistics & numerical data*; D011613:Psychotherapy / Q000706:statistics & numerical data*; D012016:Reference Values