multibalance.plot

A graphic based upon [cv.bal.psa()] function in the `PSAgraphics`
package. This graphic plots the effect sizes for multiple covariates before and
after propensity score adjustment.

Propensity score matching for non-binary treatments.

Jason Bryer

TriMatch

Propensity Score Matching of Non-Binary Treatments

multibalance.plot function

<dl><dt>tpsa</dt>
<dd>results of [trips()].</dd>
<dt>tmatch</dt>
<dd>results of [trimatch()].</dd>
<dt>grid</dt>
<dd>if TRUE, then a grid of three plots for each model will be displayed.</dd>
<dt>cols</dt>
<dd>character vector of covariates (i.e. column names) from the original 
data to include in the plot. By default all covariates used in the
logistic regression model are used.</dd></dl>

Arguments

Multiple covariate balance assessment plot. — multibalance.plot

<dl>

<dt>tpsa</dt>
<dd>results of [trips()].</dd>


<dt>tmatch</dt>
<dd>results of [trimatch()].</dd>


<dt>grid</dt>
<dd>if TRUE, then a grid of three plots for each model will be displayed.</dd>


<dt>cols</dt>
<dd>character vector of covariates (i.e. column names) from the original 
data to include in the plot. By default all covariates used in the
logistic regression model are used.</dd>

</dl>

multibalance.plot: Multiple covariate balance assessment plot.

Description

Usage

Value

Arguments