Literature DB >> 17688497

Demystifying optimal dynamic treatment regimes.

Erica E M Moodie1, Thomas S Richardson, David A Stephens.   

Abstract

A dynamic regime is a function that takes treatment and covariate history and baseline covariates as inputs and returns a decision to be made. Murphy (2003, Journal of the Royal Statistical Society, Series B 65, 331-366) and Robins (2004, Proceedings of the Second Seattle Symposium on Biostatistics, 189-326) have proposed models and developed semiparametric methods for making inference about the optimal regime in a multi-interval trial that provide clear advantages over traditional parametric approaches. We show that Murphy's model is a special case of Robins's and that the methods are closely related but not equivalent. Interesting features of the methods are highlighted using the Multicenter AIDS Cohort Study and through simulation.

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Year:  2007        PMID: 17688497     DOI: 10.1111/j.1541-0420.2006.00686.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  77 in total

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Review 9.  Inference for non-regular parameters in optimal dynamic treatment regimes.

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10.  Deep Reinforcement Learning for Dynamic Treatment Regimes on Medical Registry Data.

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Journal:  Healthc Inform       Date:  2017-08
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