Fong Youyi, Huang Ying, Gilbert Peter B, Permar Sallie R
Department of Biostatistics, Bioinformatics and Epidemiology, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, USA, 1100 Fairview Ave N., Seattle, USA.
Human Vaccine Institute, Duke University Medical Center, 2 Genome Court, Durham, USA.
BMC Bioinformatics. 2017 Oct 16;18(1):454. doi: 10.1186/s12859-017-1863-x.
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.
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.
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.
阈值回归模型是一组多样的非正则回归模型，它们都依赖于变化点或阈值。它们提供了一种简单但优雅且可解释的方式来对结果与预测变量之间的某些非线性关系进行建模。
R 包 chngpt 为阈值回归模型的四种常见变体提供了估计和假设检验功能。所有这些功能都允许对不受阈值影响的其他协变量进行调整。我们通过蒙特卡罗研究证明了估计程序的一致性和检验程序的一类错误率，并使用来自 HIV-1 病毒母婴传播背景下免疫反应生物标志物研究的一个例子说明了它们的实际用途。
chngpt 对阈值回归模型软件做出了多项独特贡献，并将使这些模型更容易被对建模阈值效应感兴趣的从业者所使用。
