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Mo, Weibin; Liu, Yufeng Efficient learning of optimal individualized treatment rules for heteroscedastic or misspecified treatment-free effect models. (English) Zbl 07593418 J. R. Stat. Soc., Ser. B, Stat. Methodol. 84, No. 2, 440-472 (2022). MSC: 62-XX PDF BibTeX XML Cite \textit{W. Mo} and \textit{Y. Liu}, J. R. Stat. Soc., Ser. B, Stat. Methodol. 84, No. 2, 440--472 (2022; Zbl 07593418) Full Text: DOI arXiv OpenURL
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Mo, Weibin; Qi, Zhengling; Liu, Yufeng Rejoinder to: “Learning optimal distributionally robust individualized treatment rules”. (English) Zbl 1464.62468 J. Am. Stat. Assoc. 116, No. 534, 699-707 (2021). MSC: 62P10 62D20 PDF BibTeX XML Cite \textit{W. Mo} et al., J. Am. Stat. Assoc. 116, No. 534, 699--707 (2021; Zbl 1464.62468) Full Text: DOI arXiv OpenURL
Mo, Weibin; Qi, Zhengling; Liu, Yufeng Learning optimal distributionally robust individualized treatment rules. (English) Zbl 1464.62467 J. Am. Stat. Assoc. 116, No. 534, 659-674 (2021). MSC: 62P10 62D20 PDF BibTeX XML Cite \textit{W. Mo} et al., J. Am. Stat. Assoc. 116, No. 534, 659--674 (2021; Zbl 1464.62467) Full Text: DOI arXiv OpenURL
Wu, Peng; Zeng, Donglin; Wang, Yuanjia Matched learning for optimizing individualized treatment strategies using electronic health records. (English) Zbl 1437.62660 J. Am. Stat. Assoc. 115, No. 529, 380-392 (2020). MSC: 62P10 68T05 PDF BibTeX XML Cite \textit{P. Wu} et al., J. Am. Stat. Assoc. 115, No. 529, 380--392 (2020; Zbl 1437.62660) Full Text: DOI Link OpenURL
Fan, Jun; Lv, Fusheng; Shi, Lei An RKHS approach to estimate individualized treatment rules based on functional predictors. (English) Zbl 1486.68149 Math. Found. Comput. 2, No. 2, 169-181 (2019). MSC: 68T05 46E22 62J02 92C50 PDF BibTeX XML Cite \textit{J. Fan} et al., Math. Found. Comput. 2, No. 2, 169--181 (2019; Zbl 1486.68149) Full Text: DOI OpenURL
Zhao, Ying-Qi; Zeng, Donglin; Tangen, Catherine M.; Leblanc, Michael L. Robustifying trial-derived optimal treatment rules for a target population. (English) Zbl 1418.62399 Electron. J. Stat. 13, No. 1, 1717-1743 (2019). MSC: 62P10 62H30 62C25 PDF BibTeX XML Cite \textit{Y.-Q. Zhao} et al., Electron. J. Stat. 13, No. 1, 1717--1743 (2019; Zbl 1418.62399) Full Text: DOI Euclid OpenURL
Zhao, Ying-Qi; Laber, Eric B.; Ning, Yang; Saha, Sumona; Sands, Bruce E. Efficient augmentation and relaxation learning for individualized treatment rules using observational data. (English) Zbl 1484.62130 J. Mach. Learn. Res. 20, Paper No. 48, 23 p. (2019). MSC: 62P10 62H30 62G05 PDF BibTeX XML Cite \textit{Y.-Q. Zhao} et al., J. Mach. Learn. Res. 20, Paper No. 48, 23 p. (2019; Zbl 1484.62130) Full Text: arXiv Link OpenURL
Kitagawa, Toru; Tetenov, Aleksey Who should be treated? Empirical welfare maximization methods for treatment choice. (English) Zbl 1419.91280 Econometrica 86, No. 2, 591-616 (2018). MSC: 91B15 62P20 PDF BibTeX XML Cite \textit{T. Kitagawa} and \textit{A. Tetenov}, Econometrica 86, No. 2, 591--616 (2018; Zbl 1419.91280) Full Text: DOI OpenURL
Butler, Emily L.; Laber, Eric B.; Davis, Sonia M.; Kosorok, Michael R. Incorporating patient preferences into estimation of optimal individualized treatment rules. (English) Zbl 1415.62088 Biometrics 74, No. 1, 18-26 (2018). MSC: 62P10 62H30 PDF BibTeX XML Cite \textit{E. L. Butler} et al., Biometrics 74, No. 1, 18--26 (2018; Zbl 1415.62088) Full Text: DOI Link OpenURL
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Zhao, Ying-Qi Outcome weighted learning methods for optimal dynamical treatment regimes. (English) Zbl 1397.92382 Kosorok, Michael R. (ed.) et al., Adaptive treatment strategies in practice. Planning trials and analyzing data for personalized medicine. Philadelphia, PA: Society for Industrial and Applied Mathematics (SIAM); Alexandria, VA: American Statistical Association (ASA) (ISBN 978-1-61197-417-1/hbk; 978-1-61197-418-8/ebook). ASA-SIAM Series on Statistics and Applied Probability 21, 119-134 (2016). MSC: 92C50 68T37 68T05 PDF BibTeX XML Cite \textit{Y.-Q. Zhao}, ASA-SIAM Ser. Stat. Appl. Probab. 21, 119--134 (2016; Zbl 1397.92382) OpenURL
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