Learn R Programming

⚠️There's a newer version (4.15) of this package.Take me there.

DynTxRegime (version 2.1)

Methods for Estimating Dynamic Treatment Regimes

Description

A comprehensive toolkit for estimating Dynamic Treatment Regimes. Available methods include Interactive Q-Learning, Q-Learning, and value-search methods based on Augmented Inverse Probability Weighted estimators and Inverse Probability Weighted estimators.

Copy Link

Version

Install

install.packages('DynTxRegime')

Monthly Downloads

3,239

Version

2.1

License

GPL-2

Maintainer

Shannon Holloway

Last Published

June 11th, 2015

Functions in DynTxRegime (2.1)

Extract Fitted Main Effects

Retrieve Regime Parameter Estimates

Retrieve Regression Objects for Propensity for Treatment

Extract Fitted Contrast Functions

Summary Results

IQ-Learning: Generate QQ-Plots for Variance Modeling .

Extract Model Coefficients

Retrieve the Result of the Genetic Algorithm Optimization

Adolescent BMI dataset (generated toy example)

Generate Standard Plots

IQ-Learning: Second-Stage Regression

DynTxRegime-class

Class "DynTxRegime"

Extract Model Residuals

IQ-Learning: Variance of First-Stage Regression of Second-Stage Contrast (IQ3)

Estimate Plug-in Value

Retrieve Regression Objects for the Outcome Regression Models

buildModelObjSubset

Create Model Objects for Subsets of Data.

IQ-Learning: First-Stage Regression of Second-Stage Estimated Contrasts

Classification Based Robust Estimation of Optimal Dynamic Treatment Regimes

Modeling Function Value Objects

Regression Based Value-Search Estimation of Optimal Dynamic Treatment Regimes

IQ-Learning: First-Stage Regression of Estimated Second-Stage Main Effects

Methods to Retrieve Estimated or to Predict Optimal Treatment

DynTxRegime-package

Methods for Estimating Dynamic Treatment Regimes

Mean Predicted Outcome

Retrieve Classification Value Object

Step of an DynTxRegime method

Standard Deviation of IQ-Learning Variance Step

Q-functions for All Treatment Options