ArticleBiometrics2018
FLCRM: Functional linear cox regression model.
Article in Biometrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- Shape-Based Partially Linear Single-Index Cox Model for Alzheimer's Disease Conversion.Statistics in medicine · 2026Article
- Joint analysis of longitudinal and recurrent event data: A functional regression approach with autoregressive frailty.Statistical methods in medical research · 2026Article
- Elastic functional Cox regression model with shape predictors.Journal of applied statistics · 2026Article
- Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.Journal of the American Statistical Association · 2026Article
- Functional varying-coefficient Cox model and its application.Statistical methods in medical research · 2026Article
- Tutorial on Bayesian Functional Regression Using Stan.Statistics in medicine · 2025Article
- Score Test for Functional Markov Process With Image Predictor.Statistics in medicine · 2025Article
- Bayesian Estimation of Partial Functional Tobit Censored Quantile Regression Model.Statistics in medicine · 2025Article
- DYNAMIC PREDICTION WITH MULTIVARIATE LONGITUDINAL OUTCOMES AND LONGITUDINAL MAGNETIC RESONANCE IMAGING DATA.The annals of applied statistics · 2025Article
- Supervised Functional Principal Component Analysis Under the Mixture Cure Rate Model: An Application to Alzheimer'S Disease.Statistics in medicine · 2025Article
- Modeling correlated pairs of mammogram images.Statistics in medicine · 2024Article
- Recurrent event analysis in the presence of real-time high frequency data via random subsampling.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2024Article
- Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces.Journal of the American Statistical Association · 2024Article
- Neural network on interval-censored data with application to the prediction of Alzheimer's disease.Biometrics · 2023Article
- Predicting the onset of breast cancer using mammogram imaging data with irregular boundary.Biostatistics (Oxford, England) · 2023Article
- Shape Analysis of Functional Data With Elastic Partial Matching.IEEE transactions on pattern analysis and machine intelligence · 2022Article
- Joint model for survival and multivariate sparse functional data with application to a study of Alzheimer's Disease.Biometrics · 2022Article
- Multi-Band Brain Network Analysis for Functional Neuroimaging Biomarker Identification.IEEE transactions on medical imaging · 2021Article
- Additive Functional Cox Model.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2021Article
- Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study.Biometrics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
We consider a functional linear Cox regression model for characterizing the association between time-to-event data and a set of functional and scalar predictors. The functional linear Cox regression model incorporates a functional principal component analysis for modeling the functional predictors and a high-dimensional Cox regression model to characterize the joint effects of both functional and scalar predictors on the time-to-event data. We develop an algorithm to calculate the maximum approximate partial likelihood estimates of unknown finite and infinite dimensional parameters. We also systematically investigate the rate of convergence of the maximum approximate partial likelihood estimates and a score test statistic for testing the nullity of the slope function associated with the functional predictors. We demonstrate our estimation and testing procedures by using simulations and the analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Our real data analyses show that high-dimensional hippocampus surface data may be an important marker for predicting time to conversion to Alzheimer's disease. Data used in the preparation of this article were obtained from the ADNI database (adni.loni.usc.edu).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.