title: Free knot splines for logistic models and threshold selection.
abstract: The logistic regression model has been in use in statistical analysis for many years. The paper introduces a spline model to remove the linear restriction on logit function. By considering knot locations as free variables, spline approximation of data is improved. The number of knots and the degree of the spline functions can still be determined by using a model selection procedure. Moreover, a knot, seen as a free parameter for a piecewise linear spline, represents a break point in the logit function which may be interpreted as a threshold value. This method is applied to a clinical trial for an in vitro fertilization program.
authors.affiliation: Laboratoire de Biostatistique, Institut Universitaire de Recherche Clinique, 641 Avenue du Doyen Gaston Giraud, 34093 Montpellier, France. bessaoud@iurc.montp.inserm.fr
authors.forename: F
authors.initials: F
authors.lastname: Bessaoud
authors.forename: J P
authors.initials: JP
authors.lastname: Daures
authors.forename: N
authors.initials: N
authors.lastname: Molinari
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D005260:Female; D005307:Fertilization in Vitro / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008297:Male; D011247:Pregnancy; D012984:Software