BFLCRM: a Bayesian functional linear Cox regression model for predicting time to conversion to Alzheimer's disease

DOI10.1214/15-AOAS879zbMath1397.62456WikidataQ36588774 ScholiaQ36588774MaRDI QIDQ262406

Hong-Tu Zhu, Eunjee Lee, Kelly Sullivan Giovanello, Joseph G. Ibrahim, Yalin Wang, Dehan Kong

Publication date: 29 March 2016

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1453994196

zbMATH Keywords

proportional hazard modelfunctional principal component analysisAlzheimer's diseasehippocampus surface morphologymild cognitive impairment

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

Varying-coefficient hidden Markov models with zero-effect regions, Joint Modeling of Longitudinal Imaging and Survival Data, Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study, A Bayesian latent spatial model for mapping the cortical signature of progression to Alzheimer's disease, Functional linear regression model with randomly censored data: predicting conversion time to Alzheimer 's disease, Modelling time-varying covariates effect on survival via functional data analysis: application to the MRC BO06 trial in osteosarcoma, Using persistent homology topological features to characterize medical images: case studies on lung and brain cancers, FLCRM: Functional linear cox regression model, BFLCRM: a Bayesian functional linear Cox regression model for predicting time to conversion to Alzheimer's disease

Uses Software

• fda (R)

Cites Work

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• Functional linear regression analysis for longitudinal data
• BFLCRM: a Bayesian functional linear Cox regression model for predicting time to conversion to Alzheimer's disease
• Oracle inequalities for the lasso in the Cox model
• Bayesian variable selection for the Cox regression model with missing covariates
• Weak convergence and optimal scaling of random walk Metropolis algorithms
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• A Bayesian justification of Cox's partial likelihood
• A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
• Estimation methods for time‐dependent AUC models with survival data
• Functional Generalized Linear Models with Images as Predictors
• Generalized Linear Models with Functional Predictors
• Bayesian Analysis and Model Selection for Interval‐Censored Survival Data
• Bayesian Measures of Model Complexity and Fit
• Statistical Advances in the Biomedical Sciences
• Monte Carlo sampling methods using Markov chains and their applications
• Bayesian survival analysis