Runze Li

Co-Director of the Center for Statistical Genetics; Eberly Family Chair and Associate Department Head in Statistics

Runze Li

Huck Affiliations

Publication Tags

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Screening Discriminant Analysis Covariates Simulation Study Predictors Model Feature Screening Performance Monte Carlo Simulation Feature Selection High Dimensional Multivariate Tests Dimensional Data Covariate Quantile Varying Coefficient Model Categorical Monte Carlo Class Statistical Inference Screening Method Ultrahigh Dimensional Data Moment Conditions Health Independence

Most Recent Publications

Projection test with sparse optimal direction for high-dimensional one-sample mean problem

Wanjun Liu, Runze Li, on p. 295-309

Reprint: Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic

Xu Guo, Runze Li, Jingyuan Liu, Mudong Zeng, 2024, Journal of Econometrics

Data science in economics and finance: Introduction

Matias D. Cattaneo, Yingying Fan, Runze Li, Rui Song, 2024, Journal of Econometrics

Propensity score regression for causal inference with treatment heterogeneity

Peng Wu, S Han, Xingwei Tong, Runze Li, 2024, Statistica Sinica

Rank-based indices for testing independence between two high-dimensional vectors

Runze Li, 2024, Annals of Statistics

Model-Free Statistical Inference on High-Dimensional Data

Xu Guo, Runze Li, Zhe Zhang, Changliang Zou, 2024, Journal of the American Statistical Association

Invariance Principle and CLT for the Spiked Eigenvalues of Large-dimensional Fisher Matrices and Applications

Dandan Jiang, Z Hou, Zhidong Bai, Runze Li, 2024, Statistica Sinica

Generalized Varying Coefficient Mediation Models

Jingyuan Liu, Yujie Liao, Runze Li, 2024, Communications in Mathematics and Statistics

Dependence motives and use contexts that predicted smoking cessation and vaping cessation: A two-year longitudinal study with 13 waves

Joon Kyung Nam, Megan E. Piper, Zhaoxue Tong, Runze Li, James J. Yang, Douglas E. Jorenby, Anne Buu, 2023, Drug and Alcohol Dependence

Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic

Xu Guo, Runze Li, Jingyuan Liu, Mudong Zeng, 2023, Journal of Econometrics on p. 166-179

Most-Cited Papers

Sensitivity and specificity of information criteria

John J. Dziak, Donna L. Coffman, Stephanie T. Lanza, Runze Li, Lars S. Jermiin, 2020, Briefings in Bioinformatics on p. 553-565

Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis

Hengjian Cui, Runze Li, Wei Zhong, 2015, Journal of the American Statistical Association on p. 630-641

Feature selection for varying coefficient models with ultrahigh-dimensional covariates

Jingyuan Liu, Runze Li, Rongling Wu, 2014, Journal of the American Statistical Association on p. 266-274

A High-Dimensional Nonparametric Multivariate Test for Mean Vector

Lan Wang, Bo Peng, Runze Li, 2015, Journal of the American Statistical Association on p. 1658-1669

Advancing the understanding of craving during smoking cessation attempts: A demonstration of the time-varying effect model

Stephanie T. Lanza, Sara A. Vasilenko, Xiaoyu Liu, Runze Li, Megan E. Piper, 2014, Nicotine and Tobacco Research on p. S127-S134

A selective overview of feature screening for ultrahigh-dimensional data

Jing Yuan Liu, Wei Zhong, Run Ze Li, 2015, Science China Mathematics

Projection correlation between two random vectors

Liping Zhu, Kai Xu, Runze Li, Wei Zhong, 2017, Biometrika on p. 829-843

Variable Screening via Quantile Partial Correlation

Shujie Ma, Runze Li, Chih Ling Tsai, 2017, Journal of the American Statistical Association on p. 650-663

Feature Screening for Ultrahigh Dimensional Categorical Data With Applications

Danyang Huang, Runze Li, Hansheng Wang, 2014, Journal of Business and Economic Statistics on p. 237-244

Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening

Rui Pan, Hansheng Wang, Runze Li, 2016, Journal of the American Statistical Association on p. 169-179