Package: cbcTools 0.5.2
cbcTools: Choice-Based Conjoint Experiment Design Generation and Power Evaluation in R
Design and evaluate choice-based conjoint survey experiments. Generate a variety of survey designs, including random designs, full factorial designs, orthogonal designs, D-optimal designs, and Bayesian D-efficient designs as well as designs with "no choice" options and "labeled" (also known as "alternative specific") 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 a power analysis for a given survey design by estimating the same model on different subsets of the data to simulate different sample sizes. Full factorial and orthogonal designs are obtained using the 'DoE.base' package (Grömping, 2018) <doi:10.18637/jss.v085.i05>. D-optimal designs are obtained using the 'AlgDesign' package (Wheeler, 2022) <https://CRAN.R-project.org/package=AlgDesign>. Bayesian D-efficient designs are obtained using the 'idefix' package (Traets et al, 2020) <doi:10.18637/jss.v096.i03>. Choice simulation and model estimation in power analyses are handled using the 'logitr' package (Helveston, 2023) <doi:10.18637/jss.v105.i10>.
Authors:
cbcTools_0.5.2.tar.gz
cbcTools_0.5.2.zip(r-4.5)cbcTools_0.5.2.zip(r-4.4)cbcTools_0.5.2.zip(r-4.3)
cbcTools_0.5.2.tgz(r-4.4-any)cbcTools_0.5.2.tgz(r-4.3-any)
cbcTools_0.5.2.tar.gz(r-4.5-noble)cbcTools_0.5.2.tar.gz(r-4.4-noble)
cbcTools_0.5.2.tgz(r-4.4-emscripten)cbcTools_0.5.2.tgz(r-4.3-emscripten)
cbcTools.pdf |cbcTools.html✨
cbcTools/json (API)
NEWS
| # Install 'cbcTools' in R: |
| install.packages('cbcTools', repos = c('https://jhelvy.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jhelvy/cbctools/issues
cbcconjointdesigndiscrete-choicesawtoothsurvey
Last updated 8 months agofrom:fb81dc4fd2. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 03 2024 |
| R-4.5-win | NOTE | Sep 03 2024 |
| R-4.5-linux | NOTE | Sep 03 2024 |
| R-4.4-win | NOTE | Sep 03 2024 |
| R-4.4-mac | NOTE | Sep 03 2024 |
| R-4.3-win | OK | Sep 03 2024 |
| R-4.3-mac | OK | Sep 03 2024 |
Exports:cbc_balancecbc_choicescbc_designcbc_overlapcbc_powercbc_profilescbc_restrictplot_compare_powerrandLNrandN
Dependencies:AlgDesignbase64encbslibcachemclicolorspacecombinatcommonmarkconf.designcrayondata.tabledfidxdigestDoE.basedplyrfansifarverfastDummiesfastmapfontawesomeFormulafsgenericsggplot2gluegmmgmpgtablehtmltoolshttpuvidefixisobandjquerylibjsonlitelabelinglaterlatticelifecyclelmtestlogitrmagrittrMASSmathjaxrMatrixmemoisemgcvmimemunsellmvtnormnlmenloptrnumberspartitionspillarpkgconfigpolynompromisesR6randtoolboxrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRdpackrlangrngWELLsandwichsassscalessetsshinysourcetoolsstringistringrtibbletidyselecttmvtnormutf8vcdvctrsviridisLitewithrxtablezoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Counts of attribute balance | cbc_balance |
| Simulate choices for a survey design | cbc_choices |
| Make a choice-based conjoint survey design | cbc_design |
| Counts of attribute overlap | cbc_overlap |
| Estimate the same model on different size subsets of data | cbc_power |
| Make a data frame of all combinations of attribute levels | cbc_profiles |
| Obtain a restricted set of profiles | cbc_restrict |
| Methods for cbc_errors objects | miscmethods.cbc_errors plot.cbc_errors |
| Methods for cbc_models objects | miscmethods.cbc_models print.cbc_models |
| Plot a comparison of different design powers | plot_compare_power |
| Define prior (assumed) model parameter as log-normally-distributed. | randLN |
| Define a prior (assumed) model parameter as normally-distributed. | randN |
