Functional varying-coefficient Cox model and its application
Fansheng Kong, Maozai Tian, Zhihao Wang, Man-lai Tang
TL;DR
This paper introduces a new survival model that handles complex data by combining varying-coefficient and functional covariates, tested on Alzheimer's data.
Contribution
The novel functional varying-coefficient Cox model improves adaptability for survival analysis with complex covariates.
Findings
The model effectively handles survival data with varying-coefficient and functional covariates.
Simulation studies confirm the model's performance improvements.
Application to ADNI data demonstrates practical utility in Alzheimer's research.
Abstract
When data become increasingly complex, desirable models are required to be more flexible for analyzing survival data. Building upon the existing functional Cox model, we introduce a novel functional varying-coefficient Cox model and the corresponding estimation algorithms are proposed in this article. The proposed model can simultaneously handle survival data with varying-coefficient covariates and functional covariates, thereby significantly enhancing the adaptability of survival models. The model performance is evaluated by simulation studies, and a real application using Alzheimer’s disease neuroimaging initiative (ADNI) data is used to illustrate the practicality of the proposed model.
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Taxonomy
TopicsStatistical Methods and Inference · Bayesian Methods and Mixture Models · Statistical Methods and Bayesian Inference