Design and Analyze Choice-Based Conjoint Experiments R package cbcTools version 0.7.1 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>. Software 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 John Helveston <john.helveston@gmail.com> Comprehensive R Archive Network (CRAN) John Helveston [cre, aut, cph] (ORCID: <https://orcid.org/0000-0002-2657-9191>) MIT + file LICENSE (https://CRAN.R-project.org/package=cbcTools/LICENSE) 2025-10-20 application/tgz https://CRAN.R-project.org/package=cbcTools doi:10.32614/CRAN.package.cbcTools