.newClassificationFit

.newClassificationFit,modelObj,TxInfoNoSubsets-method

.newClassificationFit,ModelObj_SubsetList,TxInfoWithSubsets-method

.newClassificationFit,modelObj,TxInfoWithSubsets-method

Methods dispatch appropriate typed fit methods based on the modeling
 object specified by the user and the feasible tx definitions.
 The value object returned depends on the underlying typed fit method.

internal

Methods to estimate dynamic treatment regimes using Interactive
Q-Learning, Q-Learning, weighted learning, and value-search methods based on
Augmented Inverse Probability Weighted Estimators and Inverse Probability
Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for
Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B.,
Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.

Shannon Holloway

DynTxRegime

Methods for Estimating Optimal Dynamic Treatment Regimes

.newClassificationFit function

<dl><dt>moClass</dt>
<dd>modeling object(s) defining the classification regression</dd>
<dt>txObj</dt>
<dd>TxObj defining the tx feasible sets</dd>
<dt>...</dt>
<dd>additional arguments. Ignored.</dd>
<dt>data</dt>
<dd>data.frame of covariates and tx received</dd>
<dt>suppress</dt>
<dd>logical indicating user's screen printing preference</dd></dl>

Arguments

Complete a Classification Regression Step — .newClassificationFit

<dl>

<dt>moClass</dt>
<dd>modeling object(s) defining the classification regression</dd>


<dt>txObj</dt>
<dd>TxObj defining the tx feasible sets</dd>


<dt>...</dt>
<dd>additional arguments. Ignored.</dd>


<dt>data</dt>
<dd>data.frame of covariates and tx received</dd>


<dt>suppress</dt>
<dd>logical indicating user's screen printing preference</dd>

</dl>

.newClassificationFit: Complete a Classification Regression Step

Description

Usage

Arguments