Package: cregg 0.3.7

cregg: Simple Conjoint Tidying, Analysis, and Visualization

Simple tidying, analysis, and visualization of conjoint (factorial) experiments, including estimation and visualization of average marginal component effects ('AMCEs') and marginal means ('MMs') for weighted and un-weighted survey data, along with useful reference category diagnostics and statistical tests. Estimation of 'AMCEs' is based upon methods described by Hainmueller, Hopkins, and Yamamoto (2014) <doi:10.1093/pan/mpt024>.

Authors:Thomas J. Leeper [aut, cre], Matthew Barnfield [ctb]

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NEWS

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

Peer review:

Bug tracker:https://github.com/leeper/cregg/issues

Datasets:
  • immigration - Immigration Conjoint Experiment Dataset from Hainmueller et. al.
  • taxes - Tax Preference Conjoint Experiment Dataset from Ballard-Rosa et al.
  • wide_conjoint - Example of a raw, "wide" conjoint dataset to demonstrate functionality of 'cj_tidy'

On CRAN:

amceconjointconjoint-analysis

12 exports 49 stars 3.10 score 41 dependencies 46 scripts 554 downloads

Last updated 4 years agofrom:090689064d. Checks:OK: 5 WARNING: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 06 2024
R-4.5-winWARNINGSep 06 2024
R-4.5-linuxWARNINGSep 06 2024
R-4.4-winOKSep 06 2024
R-4.4-macOKSep 06 2024
R-4.3-winOKSep 06 2024
R-4.3-macOKSep 06 2024

Exports:amceamce_by_referenceamce_diffscjcj_anovacj_dfcj_freqscj_propscj_tablecj_tidymmmm_diffs

Dependencies:clicolorspaceDBIfansifarverggplot2ggstancegluegtableisobandlabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvminqamitoolsmunsellnlmenumDerivpillarpkgconfigplyrR6RColorBrewerRcppRcppArmadillorlangsandwichscalessurveysurvivaltibbleutf8vctrsviridisLitewithrzoo

Introduction to cregg

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Sep 06 2024.

Last update: 2020-05-18
Started: 2018-02-15