Efficient interaction selection for clustered data via stagewise generalized estimating equations

DOI10.1002/sim.8574zbMATH Open1546.6277MaRDI QIDQ6627550

Jun Yan, Robert Aseltine, Gregory Vaughan, Kun Chen

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

model selectionsparsitypenalized regressionnon-Gaussian datainteraction modeling

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

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• Longitudinal data analysis using generalized linear models
• Exact post-selection inference, with application to the Lasso
• Valid post-selection inference
• A lasso for hierarchical interactions
• Statistics for high-dimensional data. Methods, theory and applications.
• The composite absolute penalties family for grouped and hierarchical variable selection
• Variable selection in strong hierarchical semiparametric models for longitudinal data
• Least angle regression. (With discussion)
• Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis
• Penalized Estimating Equations
• Semiparametric Regression for Clustered Data Using Generalized Estimating Equations
• Nonparametric Function Estimation for Clustered Data When the Predictor is Measured without/with Error
• Stagewise generalized estimating equations with grouped variables
• Shrinkage Estimation of the Varying Coefficient Model
• EEBoost: A General Method for Prediction and Variable Selection Based on Estimating Equations
• Structured sparsity through convex optimization
• A selective review of group selection in high-dimensional models

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