Package: cjbart
Title: Heterogeneous Effects Analysis of Conjoint Experiments
Version: 0.2.2
Authors@R: c(
    person(given = "Thomas",
           family = "Robinson",
           role = c("aut", "cre", "cph"),
           email = "ts.robinson1994@gmail.com",
           comment = c(ORCID = "0000-0001-7097-1599")),
    person(given = "Raymond",
           family = "Duch",
           role = c("aut","cph"),
           email = "raymond.duch@nuffield.ox.ac.uk",
           comment = c(ORCID = "0000-0002-1166-7674"))
    )
Description: 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.
License: Apache License (>= 2.0)
Encoding: UTF-8
RoxygenNote: 7.1.2
Depends: R (>= 3.6.0), BART
Imports: stats, rlang, tidyr, ggplot2, randomForestSRC, Rdpack
Suggests: testthat, knitr, cregg, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/tsrobinson/cjbart
BugReports: https://github.com/tsrobinson/cjbart/issues
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2022-03-02 11:00:42 UTC; tomrobinson
Author: Thomas Robinson [aut, cre, cph]
    (<https://orcid.org/0000-0001-7097-1599>),
  Raymond Duch [aut, cph] (<https://orcid.org/0000-0002-1166-7674>)
Maintainer: Thomas Robinson <ts.robinson1994@gmail.com>
Repository: CRAN
Date/Publication: 2022-03-02 14:20:18 UTC
Built: R 4.0.5; ; 2022-03-03 12:01:13 UTC; unix
