Dynamic Treatment Regimen Estimation via Regression-Based Techniques: Introducing R Package DTRreg
Michael P. Wallace,
Erica E. M. Moodie and
David A. Stephens
Journal of Statistical Software, 2017, vol. 080, issue i02
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.
Date: 2017-08-31
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v080i02/v80i02.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... 02/DTRreg_1.3.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v080i02/v80i02.R
https://www.jstatsoft.org/index.php/jss/article/do ... ated_PROBIT_data.csv
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:080:i02
DOI: 10.18637/jss.v080.i02
Access Statistics for this article
Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis
More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum (baum@bc.edu).