c,SubProbInfo-method

c,NodeInfo-method

c,ArcInfo-method

c,MCFSolutions-method

c,FullmatchMCFSolutions-method

Distance based bipartite matching using minimum cost flow, oriented
to matching of treatment and control groups in observational studies ('Hansen'
and 'Klopfer' 2006 <doi:10.1198/106186006X137047>). Routines are provided to
generate distances from generalised linear models (propensity score
matching), formulas giving variables on which to limit matched distances,
stratified or exact matching directives, or calipers, alone or in
combination.

Josh Errickson

optmatch

Functions for Optimal Matching

Ben Hansen

Mark Fredrickson

Josh Buckner

Adam Rauh

c,SubProbInfo-method function

<dl><dt>x</dt>
<dd>object of particular class</dd>
<dt>...</dt>
<dd>Various objects</dd></dl>

Arguments

Combine objects — c,SubProbInfo-method

<dl>

<dt>x</dt>
<dd>object of particular class</dd>


<dt>...</dt>
<dd>Various objects</dd>

</dl>

Combine objects

c,SubProbInfo-method: Combine objects

Description

Usage

Value

Arguments