Free knot splines for logistic models and threshold selection
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Updated: Aug 18, 2026

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
Published on: April 16, 2017
F Bessaoud1, J P Daures, N Molinari
1Laboratoire de Biostatistique, Institut Universitaire de Recherche Clinique, 641 Avenue du Doyen Gaston Giraud, 34093 Montpellier, France. bessaoud@iurc.montp.inserm.fr
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.
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