Leveraging mixed-effects regression trees for the analysis of high-dimensional longitudinal data to identify the low and high-risk subgroups: simulation study with application to genetic study

被引：0
|
作者：
Mina Jahangiri [1 ]
Anoshirvan Kazemnejad [1 ]
Keith S. Goldfeld [2 ]
Maryam S. Daneshpour [3 ]
Mehdi Momen [4 ]
Shayan Mostafaei [5 ]
Davood Khalili [6 ]
Mahdi Akbarzadeh [3 ]
机构：
[1] Tarbiat Modares University,Department of Biostatistics, Faculty of Medical Sciences
[2] NYU Grossman School of Medicine,Division of Biostatistics, Department of Population Health
[3] Shahid Beheshti University of Medical Sciences,Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences
[4] University of Wisconsin-Madison,Department of Surgical Sciences, School of Veterinary Medicine
[5] Karolinska Institute,Department of Medical Epidemiology and Biostatistics
[6] Shahid Beheshti University of Medical Sciences,Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences
来源：
BioData Mining | / 18卷 / 1期
关键词：
Mixed-effects model; Regression tree; Longitudinal data; High-dimensional data; Genetic study;
D O I：
10.1186/s13040-025-00437-w
中图分类号：
学科分类号：
摘要：
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