ITRLearn-package: Statistical Learing for Individualized Treatment Regime

Description Details Author(s) References


Maximin-projection learning (MPL, Shi, et al., 2018) is implemented for recommending a meaningful and reliable individualized treatment regime for future groups of patients based on the observed data from different populations with heterogeneity in individualized decision making. Q-learning and A-learning are implemented for estimating the groupwise contrast function that shares the same marginal treatment effects. The packages contains classical Q-learning and A-learning algorithms for a single stage study as a byproduct.


Package: ITRLearn
Type: Package
Version: 1.0-1
Date: 2018-11-14
License: GPL-2


Chengchun Shi, Rui Song, Wenbin Lu and Bo Fu

Maintainer: Chengchun Shi <>


Shi, C., Song, R., Lu, W., and Fu, B. (2018). Maximin Projection Learning for Optimal Treatment Decision with Heterogeneous Individualized Treatment Effects. Journal of the Royal Statistical Society, Series B, 80: 681-702.

ITRLearn documentation built on May 2, 2019, 11:03 a.m.