chngpt

BACKGROUND: Threshold regression models are a diverse set of non-regular
regression models that all depend on change points or thresholds. They provide a
simple but elegant and interpretable way to model certain kinds of nonlinear
relationships between the outcome and a predictor. RESULTS: The R package chngpt
provides both estimation and hypothesis testing functionalities for four common
variants of threshold regression models. All allow for adjustment of additional
covariates not subjected to thresholding. We demonstrate the consistency of the
estimating procedures and the type 1 error rates of the testing procedures by
Monte Carlo studies, and illustrate their practical uses using an example from
the study of immune response biomarkers in the context of
Mother-To-Child-Transmission of HIV-1 viruses. CONCLUSION: chngpt makes several
unique contributions to the software for threshold regression models and will
make these models more accessible to practitioners interested in modeling
threshold effects.

chngpt: threshold regression model estimation and inference.

chngpt is an R tool to estimate and test hypotheses of threshold regression models. The chngpt algorithms include functions for continuous and discontinuous threshold models.

chngpt

Topic

Detail

Publications

Download and documentation