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.
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.
| Original language | English |
|---|---|
| Journal | Statistical Methods in Medical Research |
| Publication status | Published - 1 Dec 2025 |
Keywords
- Functional data
- Varying-coefficients
- Cox model