Statistical Learning for Individualized Treatment Regime
Description
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. More functions will be added
at later versions.