A free-knot spline modeling framework for piecewise linear logistic regression in complex samples with body mass index and mortality as an example.

ABSTRACT: This paper details the design, evaluation, and implementation of a framework for detecting and modeling nonlinearity between a binary outcome and a continuous predictor variable adjusted for covariates in complex samples. The framework provides familiar-looking parameterizations of output in terms of linear slope coefficients and odds ratios. Estimation methods focus on maximum likelihood optimization of piecewise linear free-knot splines formulated as B-splines. Correctly specifying the optimal number and positions of the knots improves the model, but is marked by computational intensity and numerical instability. Our inference methods utilize both parametric and nonparametric bootstrapping. Unlike other nonlinear modeling packages, this framework is designed to incorporate multistage sur

SUBMITTER: Keith SW 

PROVIDER: S-EPMC4297674 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature