title: The maxslope taxometric procedure: mathematical derivation, parameter estimation, consistency tests.
abstract: This article first explains concepts in taxometrics, including the meaning of "taxon" in relation to taxometric procedures. It then mathematically develops the MAXSLOPE procedure of Grove and Meehl which relies on nonlinear regression of one taxometric indicator variable on another. Sufficient conditions for MAXSLOPE's validity are set forth. The relationship between the point of maximum regression slope (MAXSLOPE point) and the HITMAX cut, i.e., the point on a variable which, if used as a diagnostic cut-off score, yields maximum classification accuracy, is analyzed. A sufficient condition is given for the MAXSLOPE point to equal the HITMAX cut; however, most distributions have different MAXSLOPE and HITMAX points. Equations and an algorithm are spelled out for making a graphical test for the existence of a taxon, estimating taxometric parameters, and conducting consistency tests; the latter serve as stringent checks on the validity of a taxonic conjecture. The plausibility of assumptions made, in deriving MAXSLOPE equations, is discussed, and the qualitative effects of violations of these assumptions are explained.
authors.affiliation: Department of Psychology, University of Minnesota, Twin Cities, 55455-0344, USA. grove001@umn.edu
authors.forename: William M
authors.initials: WM
authors.lastname: Grove
mesh_terms: D002965:Classification / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical; D011584:Psychology / Q000379:methods / Q000706:statistics & numerical data; D015203:Reproducibility of Results