Package: ExpertChoice 0.2.1

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>.

Authors:Jed Stephens [aut, cre]

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ExpertChoice.pdf |ExpertChoice.html✨
ExpertChoice/json (API)

# Install 'ExpertChoice' in R:
install.packages('ExpertChoice', repos = c('https://jedstephens.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jedstephens/expertchoice/issues

On CRAN:

Conda:

4.88 score 15 stars 4 scripts 199 downloads 1 mentions 8 exports 41 dependencies

Last updated 5 years agofrom:dda9602c4c. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 13 2025
R-4.5-winOKFeb 13 2025
R-4.5-macOKFeb 13 2025
R-4.5-linuxOKFeb 13 2025
R-4.4-winOKFeb 13 2025
R-4.4-macOKFeb 13 2025
R-4.3-winOKFeb 13 2025
R-4.3-macOKFeb 13 2025

Exports:augment_levelscheck_overshadowconstruct_question_framedce_efficiencyfractional_factorial_efficiencyfull_factorialmodulo_methodsearch_design

Dependencies:clicolorspacecombinatconf.designdata.tableDoE.basedplyrfansifargenericsgluegmpjsonlitelatticelifecyclelmtestmagrittrMASSmathjaxrnlmenumberspartitionspillarpkgconfigpolynompurrrR6rbibutilsRdpackrlangrlistsetstibbletidyselectutf8vcdvctrswithrXMLyamlzoo

Practical Introduction to ExpertChoice

Rendered frompractical.Rmdusingknitr::rmarkdownon Feb 13 2025.

Last update: 2020-03-31
Started: 2019-11-21