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ITRSelect (version 1.0-1)

Variable Selection for Optimal Individualized Dynamic Treatment Regime

Description

Sequential advantage selection (SAS, Fan, Lu and Song, 2016) and penalized A-learning (PAL, Shi, et al., 2018) methods are implement for selecting important variables involved in optimal individualized (dynamic) treatment regime in both single-stage or multi-stage studies.

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Version

Install

install.packages('ITRSelect')

Monthly Downloads

27

Version

1.0-1

License

GPL-2

Maintainer

Chengchun Shi Developer

Last Published

September 24th, 2018

Functions in ITRSelect (1.0-1)

TR

Individualized treatment regime based on PAL or SAS.
SSTARD.onestage

Simulated single-stage dataset from the STAR*D study
SAS

Sequential advantage selection for optimal dynamic treatment regime
PAL

Penalized A-learning for optimal dynamic treatment regime
PAL.control

Control parameters for penalized A-learning
ITRSelect-package

Variable Selection for Optimal Individualized Dynamic Treatment Regime
SSTARD.twostage

Simulated two-stage dataset from the STAR*D study