Dynamic prediction with time-dependent marker in survival analysis using supervised functional principal component analysis

Cites Work

Unnamed Item
Unnamed Item
Sparse functional principal component analysis in a new regression framework
Functions of positive and negative type, and their connection with the theory of integral equations.
Modeling survival data: extending the Cox model
Dynamic prediction of disease progression for leukemia patients by functional principal component analysis of longitudinal expression levels of an oncogene
Supervised functional principal component analysis
Unified methods for censored longitudinal data and causality
Functional data analysis.
Nonparametric functional data analysis. Theory and practice.
Interpretable functional principal component analysis
Joint Models for Longitudinal and Time-to-Event Data
Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time‐to‐event in presence of censoring and competing risks
Quantifying the Predictive Performance of Prognostic Models for Censored Survival Data with Time-Dependent Covariates
Estimation methods for time‐dependent AUC models with survival data
Localized Functional Principal Component Analysis
Functional Data Analysis for Sparse Longitudinal Data
Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study
Correlation-adjusted regression survival scores for high-dimensional variable selection
Functional ensemble survival tree: dynamic prediction of Alzheimer's disease progression accommodating multiple time-varying covariates

This page was built for publication: Dynamic prediction with time-dependent marker in survival analysis using supervised functional principal component analysis