tMdat

A simulate dataset for demonstrating the functions in the twangMediation
package.

datasets

Provides functions for estimating natural direct and indirect effects for mediation analysis. It uses weighting where the weights are functions of estimates of the probability of exposure or treatment assignment (Hong, G (2010). <https://cepa.stanford.edu/sites/default/files/workshops/GH_JSM%20Proceedings%202010.pdf> Huber, M. (2014). <doi:10.1002/jae.2341>). Estimation of probabilities can use generalized boosting or logistic regression. Additional functions provide diagnostics of the model fit and weights. The vignette provides details and examples.

Dan McCaffrey

twangMediation

Twang Causal Mediation Modeling via Weighting

Katherine Castellano

Donna Coffman

Brian Vegetabile

Megan Schuler

Haoyu Zhou

tMdat function

A data frame with 500 rows and 7 variables:<dl>
<dt>w1</dt>
<dd>Simulated continuous covariate</dd><dt>w2</dt>
<dd>Simulated continuous covariate</dd><dt>w3</dt>
<dd>Simulated continuous covariate</dd><dt>A</dt>
<dd>Simulated dichotomous exposure indicator</dd><dt>Y</dt>
<dd>Simulated continuous outcome</dd><dt>M</dt>
<dd>Simulated mediator that has 11 unique values</dd><dt>te.wgt</dt>
<dd>Estimated inverse probability weight, estimated using GBM via the twang ps function</dd>
</dl>

Format

Simulated data for twangMediation — tMdat

A data frame with 500 rows and 7 variables:<dl>
<dt>w1</dt>
<dd>Simulated continuous covariate</dd>

<dt>w2</dt>
<dd>Simulated continuous covariate</dd>

<dt>w3</dt>
<dd>Simulated continuous covariate</dd>

<dt>A</dt>
<dd>Simulated dichotomous exposure indicator</dd>

<dt>Y</dt>
<dd>Simulated continuous outcome</dd>

<dt>M</dt>
<dd>Simulated mediator that has 11 unique values</dd>

<dt>te.wgt</dt>
<dd>Estimated inverse probability weight, estimated using GBM via the twang ps function</dd>


</dl>

tMdat: Simulated data for twangMediation

Description

Usage

Arguments

Value

Format

See Also

Examples