balance.matching

This function is function is primarily used by [PSAboot::balance()] and
probably does not need to be called directly.

It is often advantageous to test a hypothesis more than once
in the context of propensity score analysis (Rosenbaum, 2012)
<doi:10.1093/biomet/ass032>. The functions in this package facilitate
bootstrapping for propensity score analysis (PSA). By default,
bootstrapping using two classification tree methods (using 'rpart' and
'ctree' functions), two matching methods (using 'Matching' and
'MatchIt' packages), and stratification with logistic regression. A
framework is described for users to implement additional propensity
score methods. Visualizations are emphasized for diagnosing balance;
exploring the correlation relationships between bootstrap samples and
methods; and to summarize results.

Jason Bryer

PSAboot

Bootstrapping for Propensity Score Analysis

balance.matching function

<dl><dt>index.treated</dt>
<dd>a vector with the index of treated rows in <code>covs</code>.</dd>
<dt>index.control</dt>
<dd>a vector with the index of control rows in <code>covs</code>.</dd>
<dt>covs</dt>
<dd>data frame or matrix of covariates. Factors should already be recoded.
See `[cv.trans.psa()]`</dd></dl>

Arguments

Returns balance for each covariate from propensity score matching. — balance.matching

<dl>

<dt>index.treated</dt>
<dd>a vector with the index of treated rows in <code>covs</code>.</dd>


<dt>index.control</dt>
<dd>a vector with the index of control rows in <code>covs</code>.</dd>


<dt>covs</dt>
<dd>data frame or matrix of covariates. Factors should already be recoded.
See `[cv.trans.psa()]`</dd>

</dl>

balance.matching: Returns balance for each covariate from propensity score matching.

Description

Usage

Value

Arguments