Works (77)

Updated: March 29th, 2024 05:01

2023 journal article

A MULTIAGENT REINFORCEMENT LEARNING FRAMEWORK FOR OFF-POLICY EVALUATION IN TWO-SIDED MARKETS

ANNALS OF APPLIED STATISTICS, 17(4), 2701–2722.

By: C. Shi*, R. Wan n, G. Song, S. Luo, H. Zhu* & R. Song n

author keywords: Multiagent system; reinforcement learning; spatiotemporal studies; policy evaluation
TL;DR: This paper considers large-scale fleet management in ride-sharing companies that involve multiple units in different areas receiving sequences of products (or treatments) over time and proposes novel estimators for mean outcomes under different products that are consistent despite the high-dimensionality of state-action space. (via Semantic Scholar)
Source: Web Of Science
Added: March 25, 2024

2023 journal article

Deep spectral Q-learning with application to mobile health

STAT, 12(1).

By: Y. Gao n, C. Shi* & R. Song n

author keywords: dynamic treatment regimes; mixed frequency data; principal component analysis; reinforcement learning
TL;DR: A deep spectral Q‐learning algorithm is proposed, which integrates principal component analysis (PCA) with deep Q‐learning to handle the mixed frequency data and proves that the mean return under the estimated optimal policy converges to that under the optimal one and establishes its rate of convergence. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: May 15, 2023

2023 journal article

Flexible inference of optimal individualized treatment strategy in covariate adjusted randomization with multiple covariates

ELECTRONIC JOURNAL OF STATISTICS, 17(1), 1344–1370.

By: T. Ghosh*, Y. Ma*, R. Song n & P. Zhong*

author keywords: Covariate adjusted randomization; estimating equations; nonparametric regression; robustness; semiparametric methods; single index model; treatment effect
TL;DR: A class of estimators is devised to consistently estimate the treatment effect function and its associated index while bypassing the estimation of the baseline response, which is subject to the curse of dimensionality. (via Semantic Scholar)
Source: Web Of Science
Added: November 20, 2023

2023 article

On Learning and Testing of Counterfactual Fairness through Data Preprocessing

Chen, H., Lu, W., Song, R., & Ghosh, P. (2023, April 12). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 4.

By: H. Chen n, W. Lu n, R. Song n & P. Ghosh*

author keywords: Causal inference; Conditional independence test; Fairness learning; Machine learning ethics; Structural causal model
TL;DR: The Fair Learning through dAta Preprocessing (FLAP) algorithm is developed to learn counterfactually fair decisions from biased training data and formalize the conditions where different data preprocessing procedures should be used to guarantee counterfactual fairness. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: May 1, 2023

2022 article

A Probit Tensor Factorization Model For Relational Learning

Liu, Y., Song, R., Lu, W., & Xiao, Y. (2022, March 10). JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, Vol. 3.

By: Y. Liu n, R. Song n, W. Lu n & Y. Xiao*

author keywords: Alternating least square; EM algorithm; Link prediction; Multi-relational data; Open-world assumption; Probit model
TL;DR: A binary tensor factorization model with probit link is proposed, which not only inherits the computation efficiency from the classic tensorfactorization model but also accounts for the binary nature of relational data. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: March 28, 2022

2022 article

Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework

Shi, C., Wang, X., Luo, S., Zhu, H., Ye, J., & Song, R. (2022, March 12). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 3.

By: C. Shi*, X. Wang*, S. Luo, H. Zhu*, J. Ye* & R. Song n

author keywords: A/B testing; Causal inference; Online experiment; Online updating; Reinforcement learning; Sequential testing
TL;DR: A reinforcement learning framework for carrying A/B testing in these experiments, while characterizing the long-term treatment effects is introduced and systematically investigates the theoretical properties of the testing procedure. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: March 28, 2022

2022 journal article

Learning a deep dual-level network for robust DeepFake detection

PATTERN RECOGNITION, 130.

author keywords: DeepFake detection; Multitask learning; Imbalanced learning; AUC optimization
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: August 15, 2022

2022 article

Off-Policy Confidence Interval Estimation with Confounded Markov Decision Process

Shi, C., Zhu, J., Ye, S., Luo, S., Zhu, H., & Song, R. (2022, October 3). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 10.

By: C. Shi*, J. Zhu*, S. Ye n, S. Luo, H. Zhu* & R. Song n

author keywords: Infinite horizons; Off-policy evaluation; Reinforcement learning; Ridesourcing platforms; Statistical inference; Unmeasured confounders
TL;DR: This paper shows that with some auxiliary variables that mediate the effect of actions on the system dynamics, the target policy's value is identifiable in a confounded Markov decision process and develops an efficient off-policy value estimator that is robust to potential model misspecification and provide rigorous uncertainty quantification. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: October 17, 2022

2022 journal article

Rule mining over knowledge graphs via reinforcement learning

KNOWLEDGE-BASED SYSTEMS, 242.

author keywords: Rule mining; Reinforcement learning; Representation learning
TL;DR: A generation-then-evaluation rule mining approach guided by reinforcement learning, which achieves state-of-the-art performance in terms of efficiency and effectiveness. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Sources: Web Of Science, ORCID
Added: May 10, 2022

2022 article

Statistical Learning for Individualized Asset Allocation

Ding, Y., Li, Y., & Song, R. (2022, November 18). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 11.

By: Y. Ding*, Y. Li* & R. Song n

author keywords: Continuous-action decision-making; High-dimensional statistical learning; Individualization; Penalized regression
TL;DR: The proposed Discretization and Regression with generalized penalty on Effect discontinuity (DROVE) approach enjoys desirable theoretical properties and allows for statistical inference of the optimal value associated with optimal decision-making. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: December 19, 2022

2022 article

Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons

Shi, C., Luo, S., Le, Y., Zhu, H., & Song, R. (2022, September 22). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 9.

By: C. Shi*, S. Luo, Y. Le*, H. Zhu* & R. Song n

author keywords: Advantage learning; Infinite horizons; Mobile health applications; Rate of convergence; Reinforcement learning
TL;DR: The aim of this paper is to develop a novel advantage learning framework in order to efficiently use pre-collected data for policy optimization and outputs a new policy whose value is guaranteed to converge at a faster rate than the policy derived based on the initial Q-estimator. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: October 11, 2022

2022 article

Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes

Zhou, Y., Wang, L., Song, R., & Zhao, T. (2022, June 28). JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 6.

By: Y. Zhou, L. Wang*, R. Song n & T. Zhao*

author keywords: Exceptional laws; Individualized decision rule; Inference; Precision medicine; Robust Method; Time-to-event data
TL;DR: This work proposes a new robust framework for estimating an optimal static or dynamic IDR with time-to-event outcomes based on an easy-to-interpret quantile criterion and proves a novel result that the proposed approach can consistently estimate the optimal value function under mild conditions even when the optimal IDR is nonunique. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: July 11, 2022

2021 journal article

Concordance and Value Information Criteria for Optimal Treatment Decision

Annals of Statistics, 49(1), 49–75.

By: C. Shi*, R. Song* & W. Lu*

author keywords: Concordance and value information criteria; optimal treatment regime; tuning parameter selection; variable selection
TL;DR: This paper studies two information criteria: the concordance and value information criteria, for variable selection in optimal treatment decision making, and considers both fixed-$p$ and high dimensional settings, and shows they are consistent in model/tuning parameter selection. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: March 22, 2021

2021 journal article

GEAR: On optimal decision making with auxiliary data

STAT, 10(1).

By: H. Cai n, R. Song n & W. Lu n

author keywords: augmented inverse propensity weighted estimation; auxiliary data; individualized treatment rule; optimal treatment decision making
TL;DR: An auGmented inverse propensity weighted Experimental and Auxiliary sample-based decision Rule (GEAR) is proposed by maximizing the augmented inverse susceptibility weighted value estimator over a class of decision rules using the experimental sample, with the primary outcome being imputed based on the auxiliary sample. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: August 9, 2021

2021 article

Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control

KDD '21: PROCEEDINGS OF THE 27TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING, pp. 1634–1644.

By: R. Wan n, X. Zhang n & R. Song n

author keywords: infectious disease control; COVID-19; sequential decision making
TL;DR: A Multi-Objective Model-based Reinforcement Learning framework to facilitate data-driven decision-making and minimize the overall long-term cost is proposed and provides a real-time decision support tool for policymakers. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: March 14, 2022

2021 article

On estimating optimal regime for treatment initiation time based on restricted mean residual lifetime

Chen, X., Song, R., Zhang, J., Adams, S. A., Sun, L., & Lu, W. (2021, August 7). BIOMETRICS, Vol. 8.

By: X. Chen*, R. Song n, J. Zhang*, S. Adams*, L. Sun & W. Lu n

author keywords: individualized treatment regime; kernel estimation; optimal treatment initiation time; time-to-event data; value function
MeSH headings : Humans; Models, Statistical; Computer Simulation
TL;DR: This article proposes to use restricted mean residual lifetime as a value function to evaluate the performance of different treatment initiation regimes, and develops a nonparametric estimator for the value function, which is consistent even when treatment initiation times are not completely observable and their distribution is unknown. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: August 16, 2021

2021 article

Online Testing of Subgroup Treatment Effects Based on Value Difference

2021 21ST IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2021), pp. 1463–1468.

By: M. Yu n, W. Lu n & R. Song n

author keywords: sequential testing; heterogeneous treatment effects
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure (OpenAlex)
Sources: Web Of Science, ORCID
Added: May 2, 2022

2021 journal article

Statistical Inference for High-Dimensional Models via Recursive Online-Score Estimation

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 116(535), 1307–1318.

By: C. Shi*, R. Song n, W. Lu n & R. Li*

author keywords: Confidence interval; Generalized linear models; Online estimation; Ultrahigh dimensions
TL;DR: A new estimation and valid inference method for single or low-dimensional regression coefficients in high-dimensional generalized linear models and it is proved the proposed CI is asymptotically narrower than the CIs constructed based on the desparsified Lasso estimator and the decorrelated score statistic. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: February 10, 2020

2021 journal article

Statistical Inference for Online Decision Making: In a Contextual Bandit Setting

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 116(533), 240–255.

By: H. Chen n, W. Lu n & R. Song n

author keywords: Epsilon-greedy; Inverse propensity weighted estimator; Model misspecification; Online decision making; Statistical inference
TL;DR: Using the martingale central limit theorem, it is shown that the online ordinary least squares estimator of model parameters is asymptotically normal and the in-sample inverse propensity weighted value estimator is asylptotic normal. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: July 27, 2020

2021 article

Statistical inference of the value function for reinforcement learning in infinite-horizon settings

Shi, C., Zhang, S., Lu, W., & Song, R. (2021, December 22). JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, Vol. 12.

By: C. Shi*, S. Zhang n, W. Lu n & R. Song n

author keywords: bidirectional asymptotics; confidence interval; infinite horizons; reinforcement learning; value function
TL;DR: The focus of this paper was to construct confidence intervals (CIs) for a policy’s value in infinite horizon settings where the number of decision points diverges to infinity and it is shown that the proposed CI achieves nominal coverage even in cases where the optimal policy is not unique. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: January 3, 2022

2020 conference paper

A New Framework for Online Testing of Heterogeneous Treatment Effect

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 34(6), 10310–10317.

By: M. Yu n, W. Lu n & R. Song n

Event: Thirty-Fourth AAAI Conference on Artificial Intelligence at New York Hilton Midtown, New York, New York, USA on February 7-12, 2020

TL;DR: The proposed test, named sequential score test (SST), is able to control type I error under continuous monitoring and detect multi-dimensional heterogeneous treatment effects and provides an online p-value calculation for SST, making it convenient for continuous monitoring. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID
Added: April 18, 2021

2020 journal article

A Sparse Random Projection-Based Test for Overall Qualitative Treatment Effects

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 115(531), 1201–1213.

By: C. Shi n, W. Lu n & R. Song n

author keywords: High-dimensional testing; Optimal treatment regime; Precision medicine; Qualitative treatment effects; Sparse random projection
TL;DR: This article considers testing the overall qualitative treatment effects of patients’ prognostic covariates in a high-dimensional setting and proposes a sample splitting method to construct the test statistic, based on a nonparametric estimator of the contrast function. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: July 29, 2019

2020 journal article

Ascertaining properties of weighting in the estimation of optimal treatment regimes under monotone missingness

STATISTICS IN MEDICINE, 39(25), 3503–3520.

By: L. Dong n, E. Laber n, Y. Goldberg*, R. Song n & S. Yang n

author keywords: augmented inverse probability weighting; dynamic treatment regimes; monotonic coarseness; outcome weighted learning; Q-learning
MeSH headings : Computer Simulation; Humans; Models, Statistical; Precision Medicine; Probability
TL;DR: The application of inverse probability weighted estimating equations as an alternative to multiple imputation in the context of monotonic missingness applies to a broad class of estimators of an optimal treatment regime including both Q‐learning and a generalization of outcome weighted learning. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 17, 2020

2020 journal article

DHPA: Dynamic Human Preference Analytics Framework— A Case Study on Taxi Drivers' Learning Curve Analysis

ACM Transactions on Intelligent Systems and Technology, 11(1).

By: M. Pan*, Y. Li*, X. Zhou*, Z. Liu*, R. Song n, H. Liu, J. Luo*, W. Huang*, Z. Tian*

author keywords: Urban computing; inverse reinforcement learning; preference dynamics
TL;DR: This work inversely learns the taxi drivers’ preferences from data and characterize the dynamics of such preferences over time, and extracts two types of features to model the decision space of drivers and learns the preferences of drivers with respect to these features. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: June 15, 2020

2020 journal article

Doubly robust inference when combining probability and non-probability samples with high dimensional data

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 1.

By: S. Yang n, J. Kim* & R. Song n

author keywords: Data integration; Double robustness; Generalizability; Penalized estimating equation; Variable selection
TL;DR: This work considers integrating a non-probability sample with a probability sample which provides high dimensional representative covariate information of the target population and proposes a two-step approach for variable selection and finite population inference. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 13, 2020

2020 journal article

Testing and Estimation of Social Network Dependence With Time to Event Data

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 115(530), 570–582.

By: L. Su n, W. Lu n, R. Song n & D. Huang*

author keywords: Cox model; EM algorithm; Social network dependence; Time-to-event data
TL;DR: A novel latent spatial autocorrelation Cox model is proposed to study social network dependence with time-to-event data and introduces a latent indicator to characterize whether a person’s survival time might be affected by his or her friends’ features. (via Semantic Scholar)
UN Sustainable Development Goal Categories
10. Reduced Inequalities (OpenAlex)
Sources: Web Of Science, ORCID
Added: July 8, 2019

2019 journal article

Determining the Number of Latent Factors in Statistical Multi-Relational Learning

Journal of Machine Learning Research, 20(23), 1–38.

By: C. Shi, W. Lu & R. Song

Source: NC State University Libraries
Added: September 27, 2020

2019 chapter

Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach

In Proceedings of the 2019 SIAM International Conference on Data Mining (pp. 783–791).

By: M. Pan, Y. Li, X. Zhou, Z. Liu, R. Song*, H. Lu, J. Luo

TL;DR: This work makes the first attempt to inversely learn the taxi drivers’ preferences from data and characterize the dynamics of such preferences over time, illustrating that self-improving drivers tend to keep adjusting their preferences to habit features to increase their earning efficiency, while keeping the preferences to profile features invariant. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 20, 2020

2019 article

ENTROPY LEARNING FOR DYNAMIC TREATMENT REGIMES

Jiang, B., Song, R., Li, J., Zeng, D., Lu, W., He, X., … Kallus, N. (2019, October). STATISTICA SINICA, Vol. 29, pp. 1633–1710.

By: B. Jiang*, R. Song n, J. Li*, D. Zeng n, W. Lu, X. He, S. Xu, J. Wang ...

author keywords: Dynamic treatment regime; entropy learning; personalized medicine
TL;DR: A entropy learning approach to estimate the optimal individualized treatment rules (ITRs) is proposed and the asymptotic distributions for the estimated rules are obtained so as to provide valid inference. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: September 30, 2019

2019 journal article

LINEAR HYPOTHESIS TESTING FOR HIGH DIMENSIONAL GENERALIZED LINEAR MODELS

ANNALS OF STATISTICS, 47(5), 2671–2703.

By: C. Shi n, R. Song n, Z. Chen n & R. Li n

author keywords: High dimensional testing; linear hypothesis; likelihood ratio statistics; score test; Wald test
TL;DR: This paper proposes constrained partial regularization method and introduces an algorithm for solving regularization problems with folded-concave penalty functions and linear constraints, and shows that the limiting null distributions of these three test statistics are χ2 distribution with the same degrees of freedom, and under local alternatives, they asymptotically follow non-central χ1 distribution. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: August 19, 2019

2019 journal article

Modelling and estimation for optimal treatment decision with interference

Stat, 8(1).

By: L. Su n, W. Lu n & R. Song n

author keywords: A-learning; interference; network; optimal treatment regimen; Q-learning
TL;DR: It is shown that the optimal treatment regimen under the proposed network‐based regression model is independent from interference, which makes its application in practice more feasible and appealing. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Crossref, ORCID
Added: January 13, 2020

2019 journal article

ON TESTING CONDITIONAL QUALITATIVE TREATMENT EFFECTS

ANNALS OF STATISTICS, 47(4), 2348–2377.

By: C. Shi n, R. Song n & W. Lu n

TL;DR: The proposed definition of CQTE does not assume any parametric form for the optimal treatment rule and plays an important role for assessing the incremental value of a set of new variables in optimal treatment decision making conditional on an existing set of prescriptive variables. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: June 17, 2019

2018 journal article

A Massive Data Framework for M-Estimators with Cubic-Rate

Journal of the American Statistical Association, 113(524), 1698–1709.

By: C. Shi n, W. Lu n & R. Song n

author keywords: Cubic rate asymptotics; Divide and conquer; M-estimators; Massive data
TL;DR: Under certain condition on the growing rate of the number of subgroups, the resulting aggregated estimators are shown to have faster convergence rate and asymptotic normal distribution, which are more tractable in both computation and inference than the original M-estimators based on pooled data. (via Semantic Scholar)
Sources: Web Of Science, ORCID, Crossref
Added: February 18, 2019

2018 journal article

Deep advantage learning for optimal dynamic treatment regime

Statistical Theory and Related Fields, 2(1), 80–88.

By: S. Liang n, W. Lu n & R. Song n

TL;DR: A deep A-learning approach to estimate optimal DTR using an inverse probability weighting method to estimate the difference between potential outcomes and results indicate that the proposed methods outperform penalised least square estimator. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Crossref, ORCID
Added: January 13, 2020

2018 journal article

Discussion of ’Optimal treatment allocations in space and time for on-line control of an emerging infectious disease’

[Review of Optimal treatment allocations in space and time for on-line control of an emerging infectious disease, by E. Laber, N. Meyer, B. Reich, K. Pacifici, J. Collazo, & J. Drake]. Journal of the Royal Statistical Society, Series C, 67(4), 775–776.

By: C. Shi, R. Song & W. Lu

Source: NC State University Libraries
Added: September 27, 2020

2018 journal article

FSEM: Functional Structural Equation Models for Twin Functional Data

Journal of the American Statistical Association, 114(525), 344–357.

By: S. Luo n, R. Song n, M. Styner*, J. Gilmore* & H. Zhu*

author keywords: Covariance function; Genetic and environmental effects; Weighted likelihood ratio test
TL;DR: A novel class of functional structural equation models (FSEMs) for dissecting functional genetic and environmental effects on twin functional data, while characterizing the varying association between functional data and covariates of interest are developed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID, Crossref
Added: July 1, 2019

2018 journal article

HIGH-DIMENSIONAL A-LEARNING FOR OPTIMAL DYNAMIC TREATMENT REGIMES

ANNALS OF STATISTICS, 46(3), 925–957.

By: C. Shi n, A. Fan n, R. Song n & W. Lu n

author keywords: A-learning; Dantzig selector; NP-dimensionality; model misspecification; optimal dynamic treatment regime; oracle inequality
TL;DR: This paper proposes a penalized multi-stage A-learning for deriving the optimal dynamic treatment regime when the number of covariates is of the non-polynomial (NP) order of the sample size and adopts the Dantzig selector which directly penalizes the A-leaning estimating equations. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 6, 2018

2018 journal article

Maximin projection learning for optimal treatment decision with heterogeneous individualized treatment effects

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 80(4), 681–702.

By: C. Shi n, R. Song*, W. Lu n & B. Fu n

author keywords: Heterogeneity; Maximin projection learning; Optimal treatment regime; Quadratically constrained linear programming
TL;DR: A new maximin projection learning method is proposed for estimating a single treatment decision rule that works reliably for a group of future patients from a possibly new subpopulation by solving a quadratically constrained linear programming problem, which can be efficiently computed by interior point methods. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: October 19, 2018

2018 journal article

Proper Inference for Value Function in High-Dimensional Q-Learning for Dynamic Treatment Regimes

Journal of the American Statistical Association, 114(527), 1404–1417.

By: W. Zhu*, D. Zeng* & R. Song n

author keywords: Hard threshold; Q-learning; Value function inference; Variable selection
TL;DR: A high-dimensional Q-learning (HQ-learning) is proposed to facilitate the inference of optimal values and parameters for optimal dynamic treatment regimes and hard thresholding is introduced in the method to eliminate the effects of the nonrespondents. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID, Crossref
Added: October 28, 2019

2018 journal article

Quantile-Optimal Treatment Regimes

Journal of the American Statistical Association, 113(523), 1243–1254.

By: L. Wang*, Y. Zhou*, R. Song n & B. Sherwood*

author keywords: Dynamic treatment regime; Nonstandard asymptotics; Optimal treatment regime; Precision medicine; Quantile criterion
TL;DR: This article proposes an alternative formulation of the estimator as a solution of an optimization problem with an estimated nuisance parameter, and derives theory involving a nonstandard convergence rate and a nonnormal limiting distribution of the quantile-optimal treatment regime. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID, Crossref
Added: October 29, 2018

2018 journal article

Sparse concordance-assisted learning for optimal treatment decision

Journal of Machine Learning Research, 18.

By: S. Liang, W. Lu, R. Song & L. Wang

Source: NC State University Libraries
Added: August 6, 2018

2017 journal article

Change-Plane Analysis for Subgroup Detection and Sample Size Calculation

Journal of the American Statistical Association, 112(518), 769–778.

By: A. Fan n, R. Song n & W. Lu n

author keywords: Change-plane analysis; Doubly robust test; Sample size calculation; Semiparametric model; Subgroup analysis
TL;DR: A change-plane technique is adopted to first test the existence of a subgroup, and then identify the subgroup if the null hypothesis on nonexistence of such a sub group is rejected. (via Semantic Scholar)
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2017 journal article

DOUBLY ROBUST ESTIMATION OF OPTIMAL TREATMENT REGIMES FOR SURVIVAL DATA-WITH APPLICATION TO AN HIV/AIDS STUDY

ANNALS OF APPLIED STATISTICS, 11(3), 1763–1786.

By: R. Jiang, W. Lu*, R. Song*, M. Hudgens & S. Naprvavnik

author keywords: Doubly robust estimation; median survival time; optimal treatment regimen; restricted mean survival time
TL;DR: A doubly robust approach to estimate optimal treatment regimes that optimize a user specified function of the survival curve, including the restricted mean survival time and the median survival time is proposed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2017 journal article

Discussion of ’Random Projection Ensemble Classification’

[Review of Random Projection Ensemble Classification, by T. Cannings & R. Samworth]. Journal of the Royal Statistical Society, Series B, 79(4), 1021.

By: C. Shi, R. Song & W. Lu

Source: NC State University Libraries
Added: September 27, 2020

2017 journal article

Optimal treatment regimes for survival endpoints using locally-efficient doubly-robust estimator from a classification perspective

Lifetime Data Analysis, 23(4), 585–604.

By: X. Bai n, A. Tsiatis n, W. Lu n & R. Song n

author keywords: Classification; Doubly-robust; Observational survival study; Optimal treatment regime; Value search
MeSH headings : Computer Simulation; Coronary Artery Bypass; Coronary Artery Disease / mortality; Coronary Artery Disease / therapy; Decision Making; Humans; Life Tables; Models, Statistical; Monte Carlo Method; Percutaneous Coronary Intervention; Survival Analysis; Treatment Outcome
TL;DR: This work derives a locally efficient, doubly robust, augmented inverse probability weighted complete case estimator for the value function with censored survival data and study the large sample properties of this estimator. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 6, 2018

2017 journal article

Principal components adjusted variable screening

COMPUTATIONAL STATISTICS & DATA ANALYSIS, 110, 134–144.

By: Z. Liu n, R. Song n, D. Zeng* & J. Zhang*

author keywords: Generalized linear models; Principal components; Variable selection; Sure screening
TL;DR: A principal components adjusted variable screening method is proposed, which uses top principal components as surrogate covariates to account for the variability of the omitted predictors in generalized linear models. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 6, 2018

2017 journal article

Semiparametric single-index model for estimating optimal individualized treatment strategy

ELECTRONIC JOURNAL OF STATISTICS, 11(1), 364–384.

By: R. Song*, S. Luo*, D. Zeng, H. Zhang, W. Lu* & Z. Li

author keywords: Personalized medicine; single index model; semi-parametric inference
TL;DR: A new semiparametric additive single-index model for estimating individualized treatment strategy that assumes a flexible and nonparametric link function for the interaction between treatment and predictive covariates is proposed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2017 journal article

Subgroup detection and sample size calculation with proportional hazards regression for survival data

Statistics in Medicine, 36(29), 4646–4659.

By: S. Kang n, W. Lu n & R. Song n

author keywords: change-plane analysis; doubly robust test; sample size calculation; subgroup detection; survival data
MeSH headings : Acquired Immunodeficiency Syndrome; Algorithms; Clinical Trials as Topic; Computer Simulation; Control Groups; Humans; Propensity Score; Proportional Hazards Models; Regression Analysis; Sample Size; Statistics, Nonparametric; Survival Analysis
TL;DR: A score‐type test for detecting the existence of the subgroup is developed, which is doubly robust against misspecification of the baseline effect model or the propensity score but not both under mild assumptions for censoring. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2016 journal article

ASYMPTOTICS FOR CHANGE-POINT MODELS UNDER VARYING DEGREES OF MIS-SPECIFICATION

ANNALS OF STATISTICS, 44(1), 153–182.

By: R. Song n, M. Banerjee n & M. Kosorok n

author keywords: Change-point; model mis-specification
TL;DR: It is found that the limiting regime depends on how quickly the alternatives approach a change-point model, and a family of 'intermediate' limits that can transition, at least qualitatively, to the limits in the two extreme scenarios are unraveled. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2016 journal article

Bayesian nonparametric estimation for dynamic treatment regimes with sequential transition times comment

Journal of the American Statistical Association, 111(515), 942–947.

By: J. Chen, Y. Liu, D. Zeng, R. Song, Y. Zhao & M. Kosorok

Source: NC State University Libraries
Added: August 6, 2018

2016 journal article

Comment

Journal of the American Statistical Association, 111(515), 942–947.

author keywords: Dynamic treatment regimes; Multi-stage chemotherapy regimes; O-learning; Q-learning
TL;DR: Two alternative methods, Q-learning and O-learning, are discussed to solve the same problem from the machine learning point of view and show that these methods can be flexible and have advantages in some situations to handle treatment heterogeneity while being robust to model misspecification. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 13, 2020

2016 journal article

Concordance-assisted learning for estimating optimal individualized treatment regimes

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 79(5), 1565–1582.

By: C. Fan*, W. Lu n, R. Song n & Y. Zhou*

author keywords: D-optimality; D-s-optimality; Group testing; Sensitivity; Specificity
TL;DR: A type of concordance function for prescribing treatment is introduced and a robust rank regression method for estimating the concordances function is proposed and a doubly robust estimator of parameters in the prescriptive index is developed under a class of monotonic index models. (via Semantic Scholar)
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2016 journal article

On estimation of optimal treatment regimes for maximizing t -year survival probability

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 79(4), 1165–1185.

By: R. Jiang n, W. Lu n, R. Song n & M. Davidian n

author keywords: Inverse probability weighted estimation; Kaplan-Meier estimator; Optimal treatment regime; Personalized medicine; Survival probability; Value function
TL;DR: This work proposes two non‐parametric estimators for the survival function of patients following a given treatment regime involving one or more decisions, i.e. the so‐called value, and introduces kernel smoothing within the estimator to improve performance. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2016 journal article

Robust learning for optimal treatment decision with NP-dimensionality

ELECTRONIC JOURNAL OF STATISTICS, 10(2), 2894–2921.

By: C. Shi n, R. Song n & W. Lu n

author keywords: Non-concave penalized likelihood; optimal treatment strategy; oracle property; variable selection
TL;DR: A robust procedure for estimating the optimal treatment regime under NP dimensionality is proposed and penalized regressions are employed with the non-concave penalty function, where the conditional mean model of the response given predictors may be misspecified. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2016 journal article

SEQUENTIAL ADVANTAGE SELECTION FOR OPTIMAL TREATMENT REGIME

ANNALS OF APPLIED STATISTICS, 10(1), 32–53.

By: A. Fan*, W. Lu* & R. Song*

author keywords: Optimal treatment regime; qualitative interaction; sequential advantage; variable selection
TL;DR: A sequential advantage selection method based on the modified S-score that selects qualitatively interacted variables sequentially, and hence excludes marginally important but jointly unimportant variables or vice versa, and can handle a large amount of covariates even if sample size is small. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2015 journal article

On sparse representation for optimal individualized treatment selection with penalized outcome weighted learning

Stat, 4(1), 59–68.

author keywords: penalization; personalized medicine; support vector machine
TL;DR: This article develops a variable selection method based on penalized outcome weighted learning through which an optimal treatment rule is considered as a classification problem where each subject is weighted proportional to his or her clinical outcome. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 13, 2020

2015 journal article

Penalized q-learning for dynamic treatment regimens

Statistica Sinica, 25(3), 901–920.

By: R. Song, W. Wang, D. Zeng & M. Kosorok

Source: NC State University Libraries
Added: August 6, 2018

2015 journal article

Structured estimation for the nonparametric Cox model

ELECTRONIC JOURNAL OF STATISTICS, 9(1), 492–534.

By: J. Bradic* & R. Song n

TL;DR: Theoretical properties of the non-parametric Cox proportional hazards model in a high dimensional non-asymptotic setting are studied and it is shown that bounded effects can lead to prediction bounds similar to the simple linear models, whereas unbounded effects can leads to larger prediction bounds. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 6, 2018

2015 journal article

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy

Statistics in Medicine, 35(8), 1245–1256.

author keywords: personalized medicine; sample size calculation; treatment regimes; nonregular asymptotics; projection confidence region
MeSH headings : Biostatistics; Computer Simulation; Confidence Intervals; Data Interpretation, Statistical; Evidence-Based Practice / statistics & numerical data; Female; Fertility; Humans; Male; Models, Statistical; Pilot Projects; Precision Medicine / statistics & numerical data; Pregnancy; Randomized Controlled Trials as Topic / statistics & numerical data; Regression Analysis; Sample Size
TL;DR: This work offers a simple and robust method for powering a single stage, two‐armed randomized clinical trial when the primary aim is estimating the optimal single stage personalized treatment strategy. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Crossref, ORCID, Web Of Science
Added: August 6, 2018

2014 journal article

Censored rank independence screening for high-dimensional survival data

Biometrika, 101(4), 799–814.

By: R. Song n, W. Lu n, S. Ma* & X. Jeng n

author keywords: High-dimensional survival data; Rank independence screening; Sure screening property
TL;DR: Simulations and an analysis of real data demonstrate that the proposed method performs competitively on survival data sets of moderate size and high-dimensional predictors, even when these are contaminated. (via Semantic Scholar)
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2014 journal article

Comment on "Dynamic treatment regimes: Technical challenges and applications"

Electronic Journal of Statistics, 8, 1290–1300.

By: Y. Goldberg, R. Song, D. Zeng & M. Kosorok

Source: NC State University Libraries
Added: August 6, 2018

2014 journal article

Comment on ”Multiscale change point inference” by Frick, Munk and Sieling

[Review of Multiscale change point inference, by K. Frick, A. Munk, & H. Sieling]. Journal of the Royal Statistical Society, Series B, 76(3), 564.

By: R. Song, M. Kosorok & J. Fine

Source: NC State University Libraries
Added: September 27, 2020

2014 journal article

Doubly robust learning for estimating individualized treatment with censored data

Biometrika, 102(1), 151–168.

author keywords: Censored data; Doubly robust estimator; Individualized treatment rule; Risk bound; Support vector machine
TL;DR: Nonparametric methods for estimating an optimal individualized treatment rule in the presence of censored data are developed and a doubly robust estimator is proposed which requires correct specification of either the censoring model or survival model but not both. (via Semantic Scholar)
Sources: Web Of Science, ORCID, Crossref
Added: August 6, 2018

2014 journal article

On varying-coefficient independence screening for high-dimensional varying-coefficient models

Statistica Sinica, 24(4), 1735–1752.

By: R. Song, F. Yi & H. Zou

Source: NC State University Libraries
Added: August 6, 2018

2013 chapter

Adaptive Q-learning

In M. Bannerjee, F. Bunea, J. Huang, V. Koltchinskii, & M. H. Maathuis (Eds.), From Probability to Statistics and Back: High-Dimensional Models and Processes (pp. 150–162). Beachwood, Ohio: Institute of Mathematical Statistics.

By: Y. Goldberg, R. Song & M. Kosorok

Ed(s): M. Bannerjee, F. Bunea, J. Huang, V. Koltchinskii & M. Maathuis

Source: NC State University Libraries
Added: September 27, 2020

2012 journal article

Integrative Prescreening in Analysis of Multiple Cancer Genomic Studies

BMC Bioinformatics, 13(168).

By: R. Song*, J. Huang* & S. Ma*

MeSH headings : Computational Biology / methods; Computer Simulation; Data Interpretation, Statistical; Gene Expression Profiling / methods; Genomics / methods; Humans; Liver Neoplasms / genetics; Neoplasms / genetics; Pancreatic Neoplasms / genetics; Reproducibility of Results; Sample Size
TL;DR: The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies and can be coupled with existing analysis methods to identify cancer markers. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: September 27, 2020

2011 journal article

Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models

Journal of the American Statistical Association, 106(494), 544–557.

By: J. Fan*, Y. Feng* & R. Song*

author keywords: Additive model; Independent learning; Nonparametric independence screening; Nonparametric regression; Sparsity; Sure independence screening; Variable selection
TL;DR: This work shows that with general nonparametric models, under some mild technical conditions, the proposed independence screening methods have a sure screening property and the extent to which the dimensionality can be reduced by independence screening is also explicitly quantified. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 20, 2020

2010 journal article

Statistical Inference for a Two-Stage Outcome-Dependent Sampling Design with a Continuous Outcome

Biometrics, 67(1), 194–202.

By: H. Zhou*, R. Song*, Y. Wu* & J. Qin*

author keywords: Biased sampling; Empirical likelihood; Outcome dependent; Sample size; Two-stage design
MeSH headings : Algorithms; Biometry / methods; Case-Control Studies; Computer Simulation; Data Interpretation, Statistical; Epidemiologic Methods; Models, Statistical; Outcome Assessment, Health Care / methods
TL;DR: A semiparametric empirical likelihood estimation for inference about the regression parameters in the proposed design of a new two-stage outcome-dependent sampling (ODS) scheme with a continuous outcome variable is developed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (OpenAlex)
Sources: Crossref, ORCID
Added: January 20, 2020

2010 journal article

Sure independence screening in generalized linear models with NP-dimensionality

The Annals of Statistics, 38(6), 3567–3604.

By: J. Fan & R. Song*

author keywords: Generalized linear models; independent learning; sure independent screening; variable selection
TL;DR: It is shown that the proposed methods also possess the sure screening property with vanishing false selection rate, which justifies the applicability of such a simple method in a wide spectrum. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 20, 2020

2009 journal article

A note on semiparametric efficient inference for two-stage outcome-dependent sampling with a continuous outcome

Biometrika, 96(1), 221–228.

By: R. Song*, H. Zhou & M. Kosorok

author keywords: Biased sampling; Empirical process; Maximum likelihood estimation; Missing data; Outcome-dependent; Profile likelihood; Two-stage sampling
TL;DR: It is shown that a certain semiparametric maximum likelihood estimator is computationally convenient and achieves the semiprametric efficient information bound. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 20, 2020

2009 journal article

Cardiac Resynchronization Therapy Reduces the Risk of Hospitalizations in Patients With Advanced Heart Failure

Circulation, 119(7), 969–977.

By: I. Anand*, P. Carson*, E. Galle*, R. Song*, J. Boehmer*, J. Ghali*, B. Jaski*, J. Lindenfeld* ...

author keywords: cardiac resynchronization therapy; defibrillators, implantable; heart failure; hospitalizations; prognosis
MeSH headings : Adult; Aged; Cardiac Pacing, Artificial; Defibrillators, Implantable; Female; Heart Failure / therapy; Hospitalization / statistics & numerical data; Humans; Male; Middle Aged
TL;DR: Use of CRT with or without a defibrillator in advanced heart failure patients was associated with marked reductions in all-cause, cardiac, and heart failure hospitalization rates in an analysis that accounted for the competing risk of mortality and unequal follow-up time. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (OpenAlex)
Sources: Crossref, ORCID
Added: January 20, 2020

2009 journal article

Joint covariate-adjusted score test statistics for recurrent events and a terminal event

Lifetime Data Analysis, 16(4), 491–508.

By: R. Song* & J. Cai*

author keywords: Frailty; Proportional hazards; Proportional rates; Recurrent events data; Semiparametric model
MeSH headings : Angiotensin-Converting Enzyme Inhibitors / therapeutic use; Computer Simulation; Data Interpretation, Statistical; Enalapril / therapeutic use; Heart Failure / drug therapy; Hospitalization; Humans; Models, Statistical; Recurrence; Treatment Outcome
TL;DR: Joint covariate-adjusted score test statistics based on joint models of recurrent events and a terminal event are proposed to improve the efficiency over tests based on covariate unadjusted model. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 20, 2020

2009 journal article

On asymptotically optimal tests under loss of identifiability in semiparametric models

The Annals of Statistics, 37(5A), 2409–2444.

By: R. Song*, M. Kosorok & J. Fine

author keywords: Change-point models; contiguous alternative; empirical processes; exponential average test; nonstandard testing problem; odds-rate models; optimal test; power; profile likelihood
TL;DR: Exponential average tests based on integrated profile likelihood are constructed and shown to be asymptotically optimal under a weighted average power criterion with respect to a prior on the nonidentifiable aspect of the model. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Crossref, ORCID
Added: January 20, 2020

2008 journal article

Proximate Cues for a Short-Distance Migratory Species: an Application of Survival Analysis

Journal of Wildlife Management, 72(2), 440–448.

By: J. Meunier*, R. Song*, R. Lutz*, D. Andersen*, K. Doherty, J. Bruggink*, E. Oppelt*

author keywords: American woodcock; Great Lakes region; migration chronology; Scolopax minor; survival analysis
TL;DR: It is suggested that woodcock use a conservative photoperiod-controlled strategy with proximate modifiers for timing of migration rather than relying on abundance of their primary food, earthworms, which may serve as a navigational aid in piloting and possibly orientation. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 20, 2020

2008 journal article

What We Want versus What We Can Get: A Closer Look at Failure Time Endpoints for Cardiovascular Studies

Journal of Biopharmaceutical Statistics, 18(2), 370–381.

By: R. Song*, T. Cook* & M. Kosorok*

author keywords: cardiovascular clinical trials; competing risks; composite endpoint; recurrent events
MeSH headings : Cardiovascular Diseases / drug therapy; Cardiovascular Diseases / mortality; Clinical Trials as Topic / methods; Clinical Trials as Topic / statistics & numerical data; Data Interpretation, Statistical; Endpoint Determination / statistics & numerical data; Humans; Models, Statistical; Treatment Outcome
TL;DR: The use of all-cause mortality and the composite endpoint as the primary endpoint is reviewed and a recurrent composite endpoint is proposed as an alternative primary endpoint. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (OpenAlex)
Sources: Crossref, ORCID
Added: January 20, 2020

2007 journal article

Inference under right censoring for transformation models with a change-point based on a covariate threshold

The Annals of Statistics, 35(3), 957–989.

By: M. Kosorok & R. Song*

author keywords: change-point models; empirical processes; nonparametric maximum; likelihood; proportional hazards model; proportional odds model; right censoring; semiparametric efficiency; transformation models
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Crossref, ORCID
Added: January 20, 2020

2007 journal article

Robust Covariate-Adjusted Log-Rank Statistics and Corresponding Sample Size Formula for Recurrent Events Data

Biometrics, 64(3), 741–750.

By: R. Song*, M. Kosorok* & J. Cai*

author keywords: local alternative; log-rank statistic; power; proportional means; recurrent events data; sample size
MeSH headings : Analysis of Variance; Biometry / methods; Clinical Trials as Topic / statistics & numerical data; Cystic Fibrosis / drug therapy; Data Interpretation, Statistical; Deoxyribonuclease I / therapeutic use; Humans; Models, Statistical; Randomized Controlled Trials as Topic / statistics & numerical data; Recombinant Proteins / therapeutic use; Sample Size; Survival Analysis
TL;DR: Robust covariate‐adjusted log‐rank statistics applied to recurrent events data with arbitrary numbers of events under independent censoring and the corresponding sample size formula are developed. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Sources: Crossref, ORCID
Added: January 20, 2020

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