setV

Utilities
setV
Set the number of cross-validation
folds as a function of effective sample size
See Phillips 2023 doi.org/10.1093/ije/dyad023

An inverse probability of censoring weighted (IPCW) targeted maximum likelihood estimator (TMLE) for evaluating a marginal point treatment effect from data where some variables were collected on only a subset of participants using a two-stage design (or marginal mean outcome for a single arm study). A TMLE for conditional parameters defined by a marginal structural model (MSM) is also available.

Susan Gruber

twoStageDesignTMLE

Targeted Maximum Likelihood Estimation for Two-Stage Study
Design

Mark van der Laan

setV function

<dl><dt>n.effective</dt>
<dd>the effective sample size</dd></dl>

Arguments

Utilities
setV
Set the number of cross-validation
folds as a function of effective sample size
See Phillips 2023 doi.org/10.1093/ije/dyad023 — setV

<dl>

<dt>n.effective</dt>
<dd>the effective sample size</dd>

</dl>

setV: Utilities setV Set the number of cross-validation folds as a function of effective sample size See Phillips 2023 doi.org/10.1093/ije/dyad023

Description

Usage

Value

Arguments