cv.trans.psa

The function <code>cv.trans.psa</code> takes a covariate data frame and replaces each 
categorical covariate of <code>n &gt;=3</code> levels with n new binary covariate columns, 
one for each level. Transforms covariate dataframe for use with the function 
<code>cv.bal.psa</code>.

Conducts and visualizes propensity score analysis for
multilevel, or clustered data. Bryer & Pruzek (2011)
<doi:10.1080/00273171.2011.636693>.

Jason Bryer

multilevelPSA

Multilevel Propensity Score Analysis

cv.trans.psa function

<dl><dt>covariates</dt>
<dd>A dataframe of covariates, presumably some factors.</dd>
<dt>fcol</dt>
<dd>An optional vector containing the factor columns in the covariate 
data frame. In <code>NULL</code> (default) routine to identify factors internally.</dd></dl>

Arguments

James E. Helmreich James.Helmreich@Marist.edu
Robert M. Pruzek RMPruzek@yahoo.com
KuangNan Xiong harryxkn@yahoo.com
Jason Bryer jason@bryer.org

Author

Transformation of Factors to Individual Levels — cv.trans.psa

<dl>

<dt>covariates</dt>
<dd>A dataframe of covariates, presumably some factors.</dd>


<dt>fcol</dt>
<dd>An optional vector containing the factor columns in the covariate 
data frame. In <code>NULL</code> (default) routine to identify factors internally.</dd>

</dl>

cv.trans.psa: Transformation of Factors to Individual Levels

Description

Usage

Arguments

Author

Details