Fps.AIWKME

Logistic regression for observed treatment used for the (S)AIWKME estimator.

Provide methods for estimating optimal treatment regimes in survival contexts
with Kaplan-Meier-like estimators when no unmeasured confounding assumption is
satisfied (Jiang, R., Lu, W., Song, R., and Davidian, M. (2017) <doi:10.1111/rssb.12201>)
and when no unmeasured confounding assumption fails to hold and a binary instrument
is available (Xia, J., Zhan, Z., Zhang, J. (2022) <arXiv:2210.05538>).

Junwen Xia

otrKM

Optimal Treatment Regimes in Survival Contexts with
Kaplan-Meier-Like Estimators

Zishu Zhan

Jingxiao Zhang

Fps.AIWKME function

<dl><dt>datalist</dt>
<dd>A list used to calculate the (S)AIWKME estimator including treatment named <code>a</code>, observed time named <code>obs.t</code>, censoring indicator (0, censored) named <code>delta</code>, and baseline covariates used to assign treatment named <code>l</code>. Notice that all the data in the datalist should be ordered by observed time.</dd></dl>

Arguments

Logistic regression for observed treatment used for the (S)AIWKME estimator. — Fps.AIWKME

<dl>

<dt>datalist</dt>
<dd>A list used to calculate the (S)AIWKME estimator including treatment named <code>a</code>, observed time named <code>obs.t</code>, censoring indicator (0, censored) named <code>delta</code>, and baseline covariates used to assign treatment named <code>l</code>. Notice that all the data in the datalist should be ordered by observed time.</dd>

</dl>

Fps.AIWKME: Logistic regression for observed treatment used for the (S)AIWKME estimator.

Description

Usage

Value

Arguments

Details

References