GEE analysis in joint mean-covariance model for high-dimensional longitudinal data with HPC
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2025.2460564
Abstract: High-dimensional covariate longitudinal data is common in various fields. However, estimating a low-dimensional parameter of interest can be challenging due to the presence of high-dimensional nuisance parameters. Traditional methods using generalized estimating equations become ineffective… read more here.
Keywords: dimensional longitudinal; longitudinal data; high dimensional; covariance ... See more keywords
Orthogonal Mixed-Effects Modeling for High-Dimensional Longitudinal Data: An Unsupervised Learning Approach
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2024.3435855
Abstract: The linear mixed-effects model is commonly utilized to interpret longitudinal data, characterizing both the global longitudinal trajectory across all observations and longitudinal trajectories within individuals. However, characterizing these trajectories in high-dimensional longitudinal data presents a… read more here.
Keywords: dimensional longitudinal; longitudinal data; high dimensional; mixed effects ... See more keywords
Model-based clustering of high-dimensional longitudinal data via regularization.
Sign Up to like & getrecommendations! Published in 2022 at "Biometrics"
DOI: 10.1111/biom.13672
Abstract: We propose a model-based clustering method for high-dimensional longitudinal data via regularization in this paper. This study was motivated by the Trial of Activity in Adolescent Girls, which aimed to examine multi-level factors related to… read more here.
Keywords: based clustering; longitudinal data; dimensional longitudinal; high dimensional ... See more keywords