predict.CBPS

newdata

Return inverse logits of fitted values (the default) or fitted values themselves

type

The CBPS package fits &#8216;covariate balancing propensity score&#8217; for use in propensity score
weighting. In the binary treatment case they can also be used for matching. This method helps to 
implement that process in a manner consistent with use of propensity scores elsewhere in optmatch; see
<code><a rd-options="" href="/link/scores?package=optmatch&version=0.9-17" data-mini-rdoc="optmatch::scores">scores</a></code> documentation.

Distance based bipartite matching using the RELAX-IV minimum cost flow solver,
oriented to matching of treatment and control groups in observational
studies. 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.

Mark Fredrickson

optmatch

Functions for Optimal Matching

predict.CBPS function

The CBPS package fits &#8216;covariate balancing propensity score&#8217; for use in propensity score
weighting. In the binary treatment case they can also be used for matching. This method helps to 
implement that process in a manner consistent with use of propensity scores elsewhere in optmatch; see
<code><a rd-options='' href='scores'>scores</a></code> documentation.

predict.CBPS: (Internal) Predict for CBPS objects

Description

Usage

Arguments

Value