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cbcTools: Design and Analyze Choice-Based Conjoint Experiments

Design and evaluate choice-based conjoint survey experiments. Generate a variety of survey designs, including random designs, frequency-based designs, and D-optimal designs, as well as "labeled" designs (also known as "alternative-specific designs"), designs with "no choice" options, and designs with dominant alternatives removed. Conveniently inspect and compare designs using a variety of metrics, including design balance, overlap, and D-error, and simulate choice data for a survey design either randomly or according to a utility model defined by user-provided prior parameters. Conduct a power analysis for a given survey design by estimating the same model on different subsets of the data to simulate different sample sizes. Bayesian D-efficient designs using the 'cea' and 'modfed' methods are obtained using the 'idefix' package by Traets et al (2020) <doi:10.18637/jss.v096.i03>. Choice simulation and model estimation in power analyses are handled using the 'logitr' package by Helveston (2023) <doi:10.18637/jss.v105.i10>.

Version:	0.7.1
Depends:	R (≥ 3.5.0)
Imports:	fastDummies,ggplot2,idefix (≥ 1.1.0),logitr (≥ 1.0.1), parallel,randtoolbox,rlang, tools, stats, utils
Suggests:	here,knitr,testthat,tibble
Published:	2025-10-20
DOI:	10.32614/CRAN.package.cbcTools
Author:	John Helveston [cre, aut, cph]
Maintainer:	John Helveston <john.helveston at gmail.com>
BugReports:	https://github.com/jhelvy/cbcTools/issues
License:	MIT + fileLICENSE
URL:	https://github.com/jhelvy/cbcTools,https://jhelvy.github.io/cbcTools/
NeedsCompilation:	no
Citation:	cbcTools citation info
Materials:	README,NEWS
CRAN checks:	cbcTools results

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