18 citations · 22 across the 7 of their papers we have counts for
7 papers
glmmPen: High Dimensional Penalized Generalized Linear Mixed Models
Hillary M. Heiling, Naim U. Rashid, Quefeng Li +1
Generalized linear mixed models (GLMMs) are widely used in research for their ability to model correlated outcomes with non-Gaussian conditional distributions. The proper selection…
Efficient Computation of High-Dimensional Penalized Generalized Linear Mixed Models by Latent Factor Modeling of the Random Effects
Hillary M. Heiling, Naim U. Rashid, Quefeng Li +3
Modern biomedical datasets are increasingly high dimensional and exhibit complex correlation structures. Generalized Linear Mixed Models (GLMMs) have long been employed to account…
Joint and Individual Component Regression
Peiyao Wang, Haodong Wang, Quefeng Li +2
Multi-group data are commonly seen in practice. Such data structure consists of data from multiple groups and can be challenging to analyze due to data heterogeneity. We propose a…
Integrative Factor Regression and Its Inference for Multimodal Data Analysis
Quefeng Li, Lexin Li
Multimodal data, where different types of data are collected from the same subjects, are fast emerging in a large variety of scientific applications. Factor analysis is commonly us…
Modeling Between-Study Heterogeneity for Improved Reproducibility in Gene Signature Selection and Clinical Prediction
Naim U. Rashid, Quefeng Li, Jen Jen Yeh +1
In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new pat…
Embracing the Blessing of Dimensionality in Factor Models
Quefeng Li, Guang Cheng, Jianqing Fan +1
Factor modeling is an essential tool for exploring intrinsic dependence structures among high-dimensional random variables. Much progress has been made for estimating the covarianc…
Robust Estimation of High-Dimensional Mean Regression
Jianqing Fan, Quefeng Li, Yuyan Wang
Data subject to heavy-tailed errors are commonly encountered in various scientific fields, especially in the modern era with explosion of massive data. To address this problem, pro…