estimate

Function for estimating causal contrasts and population means using the output from <code>sbw</code>.

Implements the Stable Balancing Weights by Zubizarreta (2015) <DOI:10.1080/01621459.2015.1023805>. These are the weights of minimum variance that approximately balance the empirical distribution of the observed covariates. For an overview, see Chattopadhyay, Hase and Zubizarreta (2020) <DOI:10.1002/sim.8659>. To solve the optimization problem in 'sbw', the default solver is 'quadprog', which is readily available through CRAN. The solver 'osqp' is also posted on CRAN. To enhance the performance of 'sbw', users are encouraged to install other solvers such as 'gurobi' and 'Rmosek', which require special installation. For the installation of gurobi and pogs, please follow the instructions at <https://www.gurobi.com/documentation/current/refman/r_ins_the_r_package.html> and <http://foges.github.io/pogs/stp/r>.

Jose Zubizarreta

Stable Balancing Weights for Causal Inference and Missing Data

Jose R. Zubizarreta

Yige Li

Kwangho Kim

Amine Allouah

Noah Greifer

estimate function

<dl><dt>object</dt>
<dd>an object from function <code>sbw</code>.</dd>
<dt>out</dt>
<dd>outcome, a vector of strings with the names of the outcome variables. The default is the <code>out</code> argument from the <code>object</code>.</dd>
<dt>digits</dt>
<dd>a scalar with the number of significant digits used to display the estimates. The default is <code>6</code>.</dd>
<dt>...</dt>
<dd>ignored arguments.</dd></dl>

Arguments

Estimate causal contrasts and population means — estimate

<dl>

<dt>object</dt>
<dd>an object from function <code>sbw</code>.</dd>


<dt>out</dt>
<dd>outcome, a vector of strings with the names of the outcome variables. The default is the <code>out</code> argument from the <code>object</code>.</dd>


<dt>digits</dt>
<dd>a scalar with the number of significant digits used to display the estimates. The default is <code>6</code>.</dd>


<dt>...</dt>
<dd>ignored arguments.</dd>

</dl>

estimate: Estimate causal contrasts and population means

Description

Usage

Value

Arguments

Examples