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Dynamic Treatment Regimen Estimation via Regression-Based Techniques: Introducing R Package DTRreg

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  • Wallace, Michael P.
  • Moodie, Erica E. M.
  • Stephens, David A.

Abstract

Personalized medicine, whereby treatments are tailored to a specific patient rather than a general disease or condition, is an area of growing interest in the fields of biostatistics, epidemiology, and beyond. Dynamic treatment regimens (DTRs) are an integral part of this framework, allowing for personalized treatment of patients with long-term conditions while accounting for both their present circumstances and medical history. The identification of the optimal DTR in any given context, however, is a non-trivial problem, and so specialized methodologies have been developed for that purpose. Here we introduce the R package DTRreg which implements two regression-based approaches: G-estimation and dynamic weighted ordinary least squares regression. We outline the theory underlying these methods, discuss the implementation of DTRreg and demonstrate its use with hypothetical and real-world inspired simulated datasets.

Suggested Citation

  • Wallace, Michael P. & Moodie, Erica E. M. & Stephens, David A., 2017. "Dynamic Treatment Regimen Estimation via Regression-Based Techniques: Introducing R Package DTRreg," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 80(i02).
    • Handle: RePEc:jss:jstsof:v:080:i02
    DOI: http://hdl.handle.net/10.18637/jss.v080.i02
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    References listed on IDEAS

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    1. Baqun Zhang & Anastasios A. Tsiatis & Eric B. Laber & Marie Davidian, 2012. "A Robust Method for Estimating Optimal Treatment Regimes," Biometrics, The International Biometric Society, vol. 68(4), pages 1010-1018, December.
    2. S. A. Murphy, 2003. "Optimal dynamic treatment regimes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 331-355, May.
    3. Baqun Zhang & Anastasios A. Tsiatis & Eric B. Laber & Marie Davidian, 2013. "Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions," Biometrika, Biometrika Trust, vol. 100(3), pages 681-694.
    4. Rich Benjamin & Moodie Erica E. M. & Stephens David A & Platt Robert W, 2010. "Model Checking with Residuals for g-estimation of Optimal Dynamic Treatment Regimes," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-24, March.
    5. Yingqi Zhao & Donglin Zeng & A. John Rush & Michael R. Kosorok, 2012. "Estimating Individualized Treatment Rules Using Outcome Weighted Learning," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(499), pages 1106-1118, September.
    6. Michael P. Wallace & Erica E. M. Moodie, 2015. "Doubly‐robust dynamic treatment regimen estimation via weighted least squares," Biometrics, The International Biometric Society, vol. 71(3), pages 636-644, September.
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