plot.cjbart

Plots observation-level or individual-level marginal component effects (OMCE and IMCE respectively). By default, all attribute-levels in the model are plotted.

A tool for analyzing conjoint experiments using Bayesian Additive Regression Trees ('BART'), a machine learning method developed by Chipman, George and McCulloch (2010) <doi:10.1214/09-AOAS285>. This tool focuses specifically on estimating, identifying, and visualizing the heterogeneity within marginal component effects, at the observation- and individual-level. It uses a variable importance measure ('VIMP') with delete-d jackknife variance estimation, following Ishwaran and Lu (2019) <doi:10.1002/sim.7803>, to obtain bias-corrected estimates of which variables drive heterogeneity in the predicted individual-level effects.

Thomas Robinson

cjbart

Heterogeneous Effects Analysis of Conjoint Experiments

Raymond Duch

plot.cjbart function

<dl><dt>x</dt>
<dd>Object of class <code>cjbart</code>, the result of running <code>IMCE()</code></dd>
<dt>covar</dt>
<dd>Character string detailing the covariate over which to analyze heterogeneous effects</dd>
<dt>plot_levels</dt>
<dd>Optional vector of conjoint attribute levels to plot. If not supplied, all attributes within the conjoint model will be plotted.</dd>
<dt>se</dt>
<dd>Boolean determining whether to show an estimated 95% confidence interval</dd>
<dt>...</dt>
<dd>Additional arguments for plotting the marginal component effects (see below).</dd></dl>

Arguments

Plot Marginal Component Effects of a cjbart Object — plot.cjbart

<dl>

<dt>x</dt>
<dd>Object of class <code>cjbart</code>, the result of running <code>IMCE()</code></dd>


<dt>covar</dt>
<dd>Character string detailing the covariate over which to analyze heterogeneous effects</dd>


<dt>plot_levels</dt>
<dd>Optional vector of conjoint attribute levels to plot. If not supplied, all attributes within the conjoint model will be plotted.</dd>


<dt>se</dt>
<dd>Boolean determining whether to show an estimated 95% confidence interval</dd>


<dt>...</dt>
<dd>Additional arguments for plotting the marginal component effects (see below).</dd>

</dl>

plot.cjbart: Plot Marginal Component Effects of a `cjbart` Object

Description

Usage

Value

Arguments