 Rui Song, PhD
Investigator Associate Professor of Statistics North Carolina State University Statistics Department Dr. Song received her PhD in Statistics from the University of Wisconsin in 2006. She is Associate Professor of Statistics at North Carolina State University. Dr. Song's current research interests include high dimensional statistical learning, semiparametric inference and application of empirical processes, and dynamic treatment regimens. |
| Adaptive Q-learning., Goldberg Y, Song R, Kosorok MR, From Probability to Statistics and Back: High-Dimensional Models and Processes -- A Festschrift in Honor of Jon A. Wellner, Volume 9, Beachwood, Ohio, p.150-162. (2013) |
| Ascertaining properties of weighting in the estimation of optimal treatment regimes under monotone missingness., Dong L, Laber E, Goldberg Y, Song R, Yang S, Stat Med, Volume 39, 2020 Nov 10, Issue 25, p.3503-3520. (2020) PubMed |
| Doubly robust inference when combining probability and non-probability samples with high dimensional data., Yang S, Kim JKwang, Song R, J R Stat Soc Series B Stat Methodol, Volume 82, 2020 Apr, Issue 2, p.445-465. (2020) PubMed |
| A sparse random projection-based test for overall qualitative treatment effects., Shi C, Lu W, Song R, J Am Stat Assoc, Volume 115, 2020, Issue 531, p.1201-1213. (2020) PubMed |
| Determining the number of latent factors in statistical multi-relational learning. , Shi C, Lu W, Song R, J Mach Learn Res, Volume 20, 2019, (2019) PubMed |
| Entropy learning for dynamic treatment regimes., Jiang B, Song R, Li J, Zeng D, Stat Sin, Volume 29, 2019, Issue 4, p.1633-1655. (2019) PubMed |
| Proper inference for value function in high-dimensional Q-learning for dynamic treatment regimes., Zhu W, Zeng D, Song R, J Am Stat Assoc, Volume 114, 2019, Issue 527, p.1404-1417. (2019) PubMed |
| Modelling and estimation for optimal treatment decision with interference., Su L, Lu W, Song R, Stat (Int Stat Inst), Volume 8, 2019, Issue 1, (2019) PubMed |
| On testing conditional qualitative treatment effects., Shi C, Song R, Lu W, Ann Stat, Volume 47, 2019 Aug, Issue 4, p.2348-2377. (2019) PubMed |
| Linear hypothesis testing for high dimensional generalized linear models., Shi C, Song R, Chen Z, Li R, Ann Stat, Volume 47, 2019 Oct, Issue 5, p.2671-2703. (2019) PubMed |
| Quantile-optimal treatment regimens., Wang L, Zhou Y, Song R, Sherwood B, J Am Stat Assoc, Volume 113, 2018, Issue 523, p.1243-1254. (2018) PubMed |
| High-dimensional A-learning for optimal dynamic treatment regimes, Shi C, Fan A, Song R, Lu W, Ann Stat, Volume 46, 2018 Jun, Issue 3, p.925-957. (2018) PubMed |
| A massive data framework for M-estimators with cubic-rate., Shi C, Lu W, Song R, J Am Stat Assoc, Volume 113, 2018, Issue 524, p.1698-1709. (2018) PubMed |
| Sparse concordance-assisted learning for optimal treatment decision., Liang S, Lu W, Song R, Wang L, J Mach Learn Res, Volume 18, 2018 Apr, (2018) PubMed |
| Maximin projection learning for optimal treatment decision with heterogeneous individualized treatment effects., Shi C, Song R, Lu W, Fu B, J R Stat Soc Series B Stat Methodol, Volume 80, 2018 Sep, Issue 4, p.681-702. (2018) PubMed |
| Deep advantage learning for optimal dynamic treatment regime., Liang S, Lu W, Song R, Stat Theory Relat Fields, Volume 2, 2018, Issue 1, p.80-88. (2018) PubMed |
| Subgroup detection and sample size calculation with proportional hazards regression for survival data., Kang S, Lu W, Song R, Stat Med, Volume 36, 2017 Dec 20, Issue 29, p.4646-4659. (2017) PubMed |
| Principal components adjusted variable screening., Liu Z, Song R, Zeng D, Zhang J, Comput Stat Data Anal, Volume 110, 2017 Jun, p.134-144. (2017) PubMed |
| Semiparametric single-index model for estimating optimal individualized treatment strategy. , Song R, Luo S, Zeng D, Zhang HHelen, Lu W, Li Z, Electron J Stat, Volume 11, 2017, Issue 1, p.364-384. (2017) PubMed |
| On estimation of optimal treatment regimes for maximizing t-year survival probability., Jiang R, Lu W, Song R, Davidian M, J R Stat Soc Series B Stat Methodol, Volume 79, 2017 Sep, Issue 4, p.1165-1185. (2017) PubMed |
| Concordance-assisted learning for estimating optimal individualized treatment regimes., Fan C, Lu W, Song R, Zhou Y, J R Stat Soc Series B Stat Methodol, Volume 79, 2017 Nov, Issue 5, p.1565-1582. (2017) PubMed |
| Change-plane analysis for subgroup detection and sample size calculation., Fan A, Song R, Lu W, J Am Stat Assoc, Volume 112, 2017, Issue 518, p.769-778. (2017) PubMed |
| Optimal treatment regimes for survival endpoints using a locally-efficient doubly-robust estimator from a classification perspective., Bai X, Tsiatis AA, Lu W, Song R, Lifetime Data Anal, Volume 23, 2017 Oct, Issue 4, p.585-604. (2017) PubMed |
| Doubly robust estimation of optimal treatment regimes for survival data-with application to an HIV/AIDS study., Jiang R, Lu W, Song R, Hudgens MG, Naprvavnik S, Ann Appl Stat, Volume 11, 2017 Sep, Issue 3, p.1763-1786. (2017) PubMed |
| Asymptotics for change-point models under varying degrees of mis-specification., Song R, Banerjee M, Kosorok MR, Ann Stat, Volume 44, 2016 Feb, Issue 1, p.153-182. (2016) PubMed |
| Sequential advantage selection for optimal treatment regime., Fan A, Lu W, Song R, Ann Appl Stat, Volume 10, 2016 Mar, Issue 1, p.32-53. (2016) PubMed |
| Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy., Laber EB, Zhao YQ, Regh T, Davidian M, Tsiatis A, Stanford JB, Zeng D, Song R, Kosorok MR, Stat Med, Volume 35, 2016 Apr 15, Issue 8, p.1245-56. (2016) PubMed |
| Comment on ``Bayesian nonparametric estimation for dynamic treatment regimes with sequential transition tmes, by Xu, Y., Muller, P. Wahed, AS and Thall, PF.'', Chen J, Liu Y, Zeng D, Song R, Zhao Y, Kosorok MR, J Am Stat Assoc, Volume 111, 2016, Issue 515, p.942-947. (2016) PubMed |
| Robust learning for optimal treatment decision with NP-dimensionality., Shi C, Song R, Lu W, Electron J Stat, Volume 10, 2016, p.2894-2921. (2016) PubMed |
| On sparse representation for optimal individualized treatment selection with penalized outcome weighted learning., Song R, Kosorok M, Zeng D, Zhao Y, Laber E, Yuan M, Stat, Volume 4, 2015, Issue 1, p.59-68. (2015) PubMed |
| On varying-coefficient independence screening for high-dimensional varying-coefficient models., Song R, Yi F, Zou H, Stat Sin, Volume 24, 2014, Issue 4, p.1735-1752. (2014) PubMed |
| Comment on "Dynamic treatment regimes: Technical challenges and applications", Goldberg Y, Song R, Zeng D, Kosorok MR, Electron J Stat, Volume 8, 2014, Issue 1, p.1290-1300. (2014) PubMed |
| Censored rank independence screening for high-dimensional survival data., Song R, Lu W, Ma S, Jeng J, Biometrika, Volume 101, 2014, Issue 4, p.799-814. (2014) PubMed |
| Song R, (2012) |