ExpertChoice: Design of Discrete Choice and Conjoint Analysis

Supports designing efficient discrete choice experiments (DCEs). Experimental designs can be formed on the basis of orthogonal arrays or search methods for optimal designs (Federov or mixed integer programs). Various methods for converting these experimental designs into a discrete choice experiment. Many efficiency measures! Draws from literature of Kuhfeld (2010) and Street et. al (2005) <doi:10.1016/j.ijresmar.2005.09.003>.

Version: 0.2.0
Depends: R (≥ 3.6.0)
Imports: stats, far, dplyr, DoE.base, rlist, purrr
Suggests: knitr, rmarkdown
Published: 2020-04-03
Author: Jed Stephens ORCID iD [aut, cre]
Maintainer: Jed Stephens <STPJED001 at myuct.ac.za>
BugReports: https://github.com/JedStephens/ExpertChoice/issues
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: ExpertChoice results

Downloads:

Reference manual: ExpertChoice.pdf
Vignettes: Practical introduction to ExpertChoice
Theoretical introduction to ExpertChoice
Package source: ExpertChoice_0.2.0.tar.gz
Windows binaries: r-devel: ExpertChoice_0.2.0.zip, r-release: ExpertChoice_0.2.0.zip, r-oldrel: ExpertChoice_0.2.0.zip
macOS binaries: r-release (arm64): ExpertChoice_0.2.0.tgz, r-release (x86_64): ExpertChoice_0.2.0.tgz, r-oldrel: ExpertChoice_0.2.0.tgz

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