Flexible inference of optimal individualized treatment strategy in covariate adjusted randomization with multiple covariates-Reference-Cited by-同舟云学术

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

Published:2023-01-01 Issue:1 Volume:17 Page:
ISSN:1935-7524
Container-title:Electronic Journal of Statistics
language:
Short-container-title:Electron. J. Statist.

Author:

Ghosh Trinetri¹,Ma Yanyuan²,Song Rui³,Zhong Pingshou⁴

Affiliation:

1. Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison

2. Department of Statistics, Pennsylvania State University

3. Department of Statistics, North Carolina State University

4. Department of Mathematics, Statistics and Computer Science, University of Illinois Chicago

Publisher

Institute of Mathematical Statistics

Subject

Statistics and Probability,Statistics, Probability and Uncertainty

Reference50 articles.

1. Zhang, B., Tsiatis, A. A., Davidian, M., Zhang, M. and Laber, E. (2012). Estimating optimal treatment regimes from a classification perspective. Stat 1 103–114.

2. Jeng, X. J., Lu, W. and Peng, H. (2018). High-dimensional inference for personalized treatment decision. Electronic journal of statistics 12 2074.

3. QI, Z. and LIU, Y. (2018). D-learning to estimate optimal individual treatment rules. Electronic Journal of Statistics 12 3601–3638.

4. QIAN, M. and MURPHY, S. A. (2011). Performance guarantees for individualized treatment rules. Annals of statistics 39 1180.

5. ROBINS, J. M. (2004). Optimal structural nested models for optimal sequential decisions. In Proceedings of the second seattle Symposium in Biostatistics 189–326. Springer.

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