activity
20172023
most citedIntegrating multi-source block-wise missing data in model selection

11 citations · 19 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2023

High-dimensional statistical inference for linkage disequilibrium score regression and its cross-ancestry extensions

Fei Xue, Bingxin Zhao

Linkage disequilibrium score regression (LDSC) has emerged as an essential tool for genetic and genomic analyses of complex traits, utilizing high-dimensional data derived from gen…

stat.ME2022

An Empirical Bayes Regression for Multi-tissue eQTL Data Analysis

Fei Xue, Hongzhe Li

The Genotype-Tissue Expression (GTEx) project collects samples from multiple human tissues to study the relationship between genetic variation or single nucleotide polymorphisms (S…

stat.ME2020★ 1 cited

Multicategory Angle-based Learning for Estimating Optimal Dynamic Treatment Regimes with Censored Data

Fei Xue, Yanqing Zhang, Wenzhuo Zhou +2

An optimal dynamic treatment regime (DTR) consists of a sequence of decision rules in maximizing long-term benefits, which is applicable for chronic diseases such as HIV infection…

stat.ME2019★ 11 cited

Integrating multi-source block-wise missing data in model selection

Fei Xue, Annie Qu

For multi-source data, blocks of variable information from certain sources are likely missing. Existing methods for handling missing data do not take structures of block-wise missi…

stat.ME2017★ 7 cited

Individualized Multi-directional Variable Selection

Xiwei Tang, Fei Xue, Annie Qu

In this paper we propose a heterogeneous modeling framework which achieves individual-wise feature selection and individualized covariates' effects subgrouping simultaneously. In c…