Researcher Profile
Researcher Profile
Runze Li, PhD
Verne M. Willaman Professor, Statistics
Professor, Department of Public Health Sciences
Director, Center for Statistical Genetics
Professor, Department of Public Health Sciences
Director, Center for Statistical Genetics
Scientific Program:Cancer Control
Research Interests
- Smoking
- Sample Size
- Substance-Related Disorders
- Ecological Momentary Assessment
- Genes
- Parkinson Disease
- Research Personnel
- Smoking Cessation
- Quantitative Trait Loci
- Alcohols
- Datasets
- Data Analysis
Recent Publications
2022
Cai, Z, Li, R & Zhang, Y 2022, 'A Distribution Free Conditional Independence Test with Applications to Causal Discovery', Journal of Machine Learning Research, vol. 23.
Bao, L, Li, C, Li, R & Yang, S 2022, 'Causal Structural Learning on MPHIA Individual Dataset', Journal of the American Statistical Association, vol. 117, no. 540, pp. 1642-1655. https://doi.org/10.1080/01621459.2022.2077209
Cai, Z, Xi, D, Zhu, X & Li, R 2022, 'Causal discoveries for high dimensional mixed data', Statistics in Medicine, vol. 41, no. 24, pp. 4924-4940. https://doi.org/10.1002/sim.9544
Na, M, Dou, N, Liao, Y, Rincon, SJ, Francis, LA, Graham-Engeland, JE, Murray-Kolb, LE & Li, R 2022, 'Daily Food Insecurity Predicts Lower Positive and Higher Negative Affect: An Ecological Momentary Assessment Study', Frontiers in Nutrition, vol. 9, 790519. https://doi.org/10.3389/fnut.2022.790519
Jimenez Rincon, S, Dou, N, Murray-Kolb, LE, Hudy, K, Mitchell, DC, Li, R & Na, M 2022, 'Daily food insecurity is associated with diet quality, but not energy intake, in winter and during COVID-19, among low-income adults', Nutrition Journal, vol. 21, no. 1, 19. https://doi.org/10.1186/s12937-022-00768-y
Cai, X, Coffman, DL, Piper, ME & Li, R 2022, 'Estimation and inference for the mediation effect in a time-varying mediation model', BMC Medical Research Methodology, vol. 22, no. 1, 113. https://doi.org/10.1186/s12874-022-01585-x
Guo, X, Li, R, Liu, J & Zeng, M 2022, 'High-Dimensional Mediation Analysis for Selecting DNA Methylation Loci Mediating Childhood Trauma and Cortisol Stress Reactivity', Journal of the American Statistical Association, vol. 117, no. 539, pp. 1110-1121. https://doi.org/10.1080/01621459.2022.2053136
Zeng, M, Liao, Y, Li, R & Sudjianto, A 2022, 'Local Linear Approximation Algorithm for Neural Network', Mathematics, vol. 10, no. 3, 494. https://doi.org/10.3390/math10030494
Tong, Z, Cai, Z, Yang, S & Li, R 2022, 'Model-Free Conditional Feature Screening with FDR Control', Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2022.2063130
Liu, W, Yu, X & Li, R 2022, 'Multiple-Splitting Projection Test for High-Dimensional Mean Vectors', Journal of Machine Learning Research, vol. 23.
Chen, Y, Wang, Y, Fang, EX, Wang, Z & Li, R 2022, 'Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection', Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2022.2108816
Yu, X, Li, D, Xue, L & Li, R 2022, 'Power-Enhanced Simultaneous Test of High-Dimensional Mean Vectors and Covariance Matrices with Application to Gene-Set Testing', Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2022.2061354
Chen, H, Zou, CL & Li, RZ 2022, 'Projection-based High-dimensional Sign Test', Acta Mathematica Sinica, English Series, vol. 38, no. 4, pp. 683-708. https://doi.org/10.1007/s10114-022-0435-9
Li, C, Li, R, Wen, J, Yang, S & Zhan, X 2022, 'Regularized Linear Programming Discriminant Rule with Folded Concave Penalty for Ultrahigh-Dimensional Data', Journal of Computational and Graphical Statistics. https://doi.org/10.1080/10618600.2022.2143785
Guo, X, Li, R, Liu, J & Zeng, M 2022, 'Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic', Journal of Econometrics. https://doi.org/10.1016/j.jeconom.2022.03.001
Brown, G, Du, G, Farace, E, Lewis, MM, Eslinger, PJ, McInerney, J, Kong, L, Li, R, Huang, X & De Jesus, S 2022, 'Subcortical Iron Accumulation Pattern May Predict Neuropsychological Outcomes after Subthalamic Nucleus Deep Brain Stimulation: A Pilot Study', Journal of Parkinson's Disease, vol. 12, no. 3, pp. 851-863. https://doi.org/10.3233/JPD-212833
Li, R, Xu, K, Zhou, Y & Zhu, L 2022, 'Testing the Effects of High-Dimensional Covariates via Aggregating Cumulative Covariances', Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2022.2044334
Yang, JJ, Lin, HC, Ou, TS, Tong, Z, Li, R, Piper, ME & Buu, A 2022, 'The situational contexts and subjective effects of co-use of electronic cigarettes and alcohol among college students: An ecological momentary assessment (EMA) study', Drug and alcohol dependence, vol. 239, 109594. https://doi.org/10.1016/j.drugalcdep.2022.109594
Guo, X, Ren, H, Zou, C & Li, R 2022, 'Threshold Selection in Feature Screening for Error Rate Control', Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2021.2011735
Ren, H, Zou, C & Li, R 2022, '大规模数据分析中基于外推的调节参数选取', Scientia Sinica Mathematica, vol. 52, no. 6, pp. 689-708. https://doi.org/10.1360/SCM-2020-0622
2021
Huang, Y, Li, C, Li, R & Yang, S 2022, 'An overview of tests on high-dimensional means', Journal of Multivariate Analysis, vol. 188, 104813. https://doi.org/10.1016/j.jmva.2021.104813
Li, Z, Wang, Q & Li, R 2021, 'Central limit theorem for linear spectral statistics of large dimensional Kendall's rank correlation matrices and its applications', Annals of Statistics, vol. 49, no. 3, pp. 1569-1593. https://doi.org/10.1214/20-AOS2013
Nandy, D, Chiaromonte, F & Li, R 2022, 'Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems', Journal of the American Statistical Association, vol. 117, no. 539, pp. 1516-1529. https://doi.org/10.1080/01621459.2020.1864380
Huang, D, Zhu, X, Li, R & Wang, H 2021, 'Feature screening for network autoregression model', Statistica Sinica, vol. 31, no. 3, pp. 1239-1259. https://doi.org/10.5705/ss.202018-0400
Li, C, Wang, X, Du, G, Chen, H, Brown, G, Lewis, MM, Yao, T, Li, R & Huang, X 2021, 'Folded concave penalized learning of high-dimensional MRI data in Parkinson's disease', Journal of Neuroscience Methods, vol. 357, 109157. https://doi.org/10.1016/j.jneumeth.2021.109157
Xiao, D, Ke, Y & Li, R 2021, 'Homogeneity structure learning in large-scale panel data with heavy-tailed errors', Journal of Machine Learning Research, vol. 22.
Li, M, Li, R & Ma, Y 2021, 'Inference in high dimensional linear measurement error models', Journal of Multivariate Analysis, vol. 184, 104759. https://doi.org/10.1016/j.jmva.2021.104759
Zou, T, Lan, W, Li, R & Tsai, CL 2022, 'Inference on covariance-mean regression', Journal of Econometrics, vol. 230, no. 2, pp. 318-338. https://doi.org/10.1016/j.jeconom.2021.05.004
Guo, X, Li, R, Liu, W & Zhu, L 2022, 'Stable correlation and robust feature screening', Science China Mathematics, vol. 65, no. 1, pp. 153-168. https://doi.org/10.1007/s11425-019-1702-5
Parikh, RB, Liu, M, Li, E, Li, R & Chen, J 2021, 'Trajectories of mortality risk among patients with cancer and associated end-of-life utilization', npj Digital Medicine, vol. 4, no. 1, 104. https://doi.org/10.1038/s41746-021-00477-6
Buu, A, Cai, Z, Li, R, Wong, SW, Lin, HC, Su, WC, Jorenby, DE & Piper, ME 2021, 'Validating E-Cigarette Dependence Scales Based on Dynamic Patterns of Vaping Behaviors', Nicotine and Tobacco Research, vol. 23, no. 9, pp. 1484-1489. https://doi.org/10.1093/ntr/ntab050
Wang, J, Cai, X & Li, R 2021, 'Variable selection for partially linear models via Bayesian subset modeling with diffusing prior', Journal of Multivariate Analysis, vol. 183, 104733. https://doi.org/10.1016/j.jmva.2021.104733
Liao, Y, Liu, J, Coffman, DL & Li, R 2022, 'Varying Coefficient Mediation Model and Application to Analysis of Behavioral Economics Data', Journal of Business and Economic Statistics, vol. 40, no. 4, pp. 1759-1771. https://doi.org/10.1080/07350015.2021.1971089
2020
Wang, L, Peng, B, Bradic, J, Li, R & Wu, Y 2020, 'A Tuning-free Robust and Efficient Approach to High-dimensional Regression', Journal of the American Statistical Association, vol. 115, no. 532, pp. 1700-1714. https://doi.org/10.1080/01621459.2020.1840989
Zou, C, Wang, G & Li, R 2020, 'Consistent selection of the number of change-points via sample-splitting', Annals of Statistics, vol. 48, no. 1, pp. 413-439. <https://projecteuclid.org/euclid.aos/1581930141>
Li, X, Li, R, Xia, Z & Xu, C 2020, 'Distributed feature screening via componentwise debiasing', Journal of Machine Learning Research, vol. 21.
Cui, X, Li, R, Yang, G & Zhou, W 2020, 'Empirical likelihood test for a large-dimensional mean vector', Biometrika, vol. 107, no. 3, pp. 591-607. https://doi.org/10.1093/biomet/asaa005
Buu, A, Yang, S, Li, R, Zimmerman, MA, Cunningham, RM & Walton, MA 2020, 'Examining measurement reactivity in daily diary data on substance use: Results from a randomized experiment', Addictive Behaviors, vol. 102, 106198. https://doi.org/10.1016/j.addbeh.2019.106198
Yang, G, Yang, S & Li, R 2020, 'Feature screening in ultrahigh-dimensional generalized varying-coefficient models', Statistica Sinica, vol. 30, no. 2, pp. 1049-1067. https://doi.org/10.5705/ss.202017.0362
Chu, W, Li, R, Liu, J & Reimherr, M 2020, 'Feature selection for generalized varying coefficient mixed-effect models with application to obesity gwas', Annals of Applied Statistics, vol. 14, no. 1, pp. 276-298. https://doi.org/10.1214/19-AOAS1310
Ren, H, Zou, C, Chen, N & Li, R 2022, 'Large-Scale Datastreams Surveillance via Pattern-Oriented-Sampling', Journal of the American Statistical Association, vol. 117, no. 538, pp. 794-808. https://doi.org/10.1080/01621459.2020.1819295
Liu, W, Ke, Y, Liu, J & Li, R 2022, 'Model-Free Feature Screening and FDR Control With Knockoff Features', Journal of the American Statistical Association, vol. 117, no. 537, pp. 428-443. https://doi.org/10.1080/01621459.2020.1783274
Zhou, T, Zhu, L, Xu, C & Li, R 2020, 'Model-Free Forward Screening Via Cumulative Divergence', Journal of the American Statistical Association, vol. 115, no. 531, pp. 1393-1405. https://doi.org/10.1080/01621459.2019.1632078
Cai, Z, Li, R & Zhu, L 2020, 'Online sufficient dimension reduction through sliced inverse regression', Journal of Machine Learning Research, vol. 21.
Yang, S, Wen, J, Eckert, ST, Wang, Y, Liu, DJ, Wu, R, Li, R & Zhan, X 2020, 'Prioritizing genetic variants in GWAS with lasso using permutation-assisted tuning', Bioinformatics, vol. 36, no. 12, pp. 3811-3817. https://doi.org/10.1093/bioinformatics/btaa229
Wang, L, Peng, B, Bradic, J, Li, R & Wu, Y 2020, 'Rejoinder to “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression”', Journal of the American Statistical Association, vol. 115, no. 532, pp. 1726-1729. https://doi.org/10.1080/01621459.2020.1843865
Dziak, JJ, Coffman, DL, Lanza, ST, Li, R & Jermiin, LS 2020, 'Sensitivity and specificity of information criteria', Briefings in bioinformatics, vol. 21, no. 2, pp. 553-565. https://doi.org/10.1093/bib/bbz016
Shi, C, Song, R, Lu, W & Li, R 2021, 'Statistical Inference for High-Dimensional Models via Recursive Online-Score Estimation', Journal of the American Statistical Association, vol. 116, no. 535, pp. 1307-1318. https://doi.org/10.1080/01621459.2019.1710154
Fang, EX, Ning, Y & Li, R 2020, 'Test of significance for high-dimensional longitudinal data', Annals of Statistics, vol. 48, no. 5, pp. 2622-2645. https://doi.org/10.1214/19-AOS1900
Buu, A, Cai, Z, Li, R, Wong, SW, Lin, HC, Su, WC, Jorenby, DE & Piper, ME 2021, 'The association between short-term emotion dynamics and cigarette dependence: A comprehensive examination of dynamic measures', Drug and alcohol dependence, vol. 218, 108341. https://doi.org/10.1016/j.drugalcdep.2020.108341
Liu, W & Li, R 2020, Variable Selection and Feature Screening. in Advanced Studies in Theoretical and Applied Econometrics. Advanced Studies in Theoretical and Applied Econometrics, vol. 52, Springer, pp. 293-326. https://doi.org/10.1007/978-3-030-31150-6_10
2019
Wang, L, Ma, J, Dholakia, R, Howells, C, Lu, Y, Chen, C, Li, R, Murray, M & Leslie, D 2019, 'Changes in healthcare expenditures after the autism insurance mandate', Research in Autism Spectrum Disorders, vol. 57, pp. 97-104. https://doi.org/10.1016/j.rasd.2018.10.004
Yang, G, Zhang, L, Li, R & Huang, Y 2019, 'Feature screening in ultrahigh-dimensional varying-coefficient Cox model', Journal of Multivariate Analysis, vol. 171, pp. 284-297. https://doi.org/10.1016/j.jmva.2018.12.009
Zhong, PS, Li, R & Santo, S 2019, 'Homogeneity tests of covariance matrices with high-dimensional longitudinal data', Biometrika, vol. 106, no. 3, pp. 619-634. https://doi.org/10.1093/biomet/asz011
Zheng, S, Chen, Z, Cui, H & Li, R 2019, 'Hypothesis testing on linear structures of high-dimensional covariance matrix', Annals of Statistics, vol. 47, no. 6, pp. 3300-3334. https://doi.org/10.1214/18-AOS1779
Shi, C, Song, R, Chen, Z & Li, R 2019, 'Linear hypothesis testing for high dimensional generalized linear models', Annals of Statistics, vol. 47, no. 5, pp. 2671-2703. https://doi.org/10.1214/18-AOS1761
Zhu, X, Chang, X, Li, R & Wang, H 2019, 'Portal nodes screening for large scale social networks', Journal of Econometrics, vol. 209, no. 2, pp. 145-157. https://doi.org/10.1016/j.jeconom.2018.12.021
Dziak, JJ, Coffman, DL, Reimherr, M, Petrovich, J, Li, R, Shiffman, S & Shiyko, MP 2019, 'Scalar-on-function regression for predicting distal outcomes from intensively gathered longitudinal data: Interpretability for applied scientists', Statistics Surveys, vol. 13, pp. 150-180. https://doi.org/10.1214/19-SS126
Li, M, Ma, Y & Li, R 2019, 'Semiparametric regression for measurement error model with heteroscedastic error', Journal of Multivariate Analysis, vol. 171, pp. 320-338. https://doi.org/10.1016/j.jmva.2018.12.012
Liu, W, Li, R, Zimmerman, MA, Walton, MA, Cunningham, RM & Buu, A 2019, 'Statistical methods for evaluating the correlation between timeline follow-back data and daily process data with applications to research on alcohol and marijuana use', Addictive Behaviors, vol. 94, pp. 147-155. https://doi.org/10.1016/j.addbeh.2018.12.024
Trucco, EM, Yang, S, Yang, JJ, Zucker, RA, Li, R & Buu, A 2020, 'Time-varying Effects of GABRG1 and Maladaptive Peer Behavior on Externalizing Behavior from Childhood to Adulthood: Testing Gene × Environment × Development Effects', Journal of youth and adolescence, vol. 49, no. 7, pp. 1351-1364. https://doi.org/10.1007/s10964-019-01171-3
Wang, L, Chen, Z, Wang, CD & Li, R 2020, 'Ultrahigh dimensional precision matrix estimation via refitted cross validation', Journal of Econometrics, vol. 215, no. 1, pp. 118-130. https://doi.org/10.1016/j.jeconom.2019.08.004