cbcTools: Design and Evaluate Choice-Based Conjoint Survey Experiments
Design and evaluate choice-based conjoint survey experiments in R. Generate survey designs, including randomized designs and Bayesian D-efficient designs as well as designs with "no choice" options and labeled designs. Conveniently inspect the design balance and overlap, and simulate choice data for a survey design either randomly or according to a multinomial or mixed logit utility model defined by user-provided prior parameters. Conduct power analyses on a survey design by estimating the same model multiple times using different subsets of the data to simulate different sample sizes. Choice simulation and model estimation are handled using the 'logitr' package, and Bayesian D-efficient designs are obtained using the 'idefix' package. For more details see Helveston (2023) <doi:10.18637/jss.v105.i10> and Traets et al (2020) <doi:10.18637/jss.v096.i03>.
Version: |
0.3.2 |
Depends: |
R (≥ 3.5.0) |
Imports: |
dplyr, fastDummies, ggplot2, idefix, logitr (≥ 1.0.1), MASS, parallel, randtoolbox, rlang, stats, utils |
Suggests: |
testthat, tibble |
Published: |
2023-05-23 |
Author: |
John Helveston
[cre, aut, cph] |
Maintainer: |
John Helveston <john.helveston at gmail.com> |
BugReports: |
https://github.com/jhelvy/cbcTools/issues |
License: |
MIT + file LICENSE |
URL: |
https://github.com/jhelvy/cbcTools |
NeedsCompilation: |
no |
Citation: |
cbcTools citation info |
Materials: |
README NEWS |
CRAN checks: |
cbcTools results |
Documentation:
Downloads:
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