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A set of functions to conduct Conjunctive Analysis of Case Configurations (CACC) as described in Miethe, Hart, and Regoeczi (2008) <doi:10.1007/s10940-008-9044-8>, and identify and quantify situational clustering in dominant case configurations as described in Hart (2019) <doi:10.1177/0011128719866123>. Initially conceived as an exploratory technique for multivariate analysis of categorical data, CACC has developed to include formal statistical tests that can be applied in a wide variety of contexts. This technique allows examining composite profiles of different units of analysis in an alternative way to variable-oriented methods.
Version: | 0.1.1 |
Depends: | R (≥ 4.1) |
Imports: | dplyr, ggplot2, rlang, stats, tibble, tidyr |
Published: | 2024-10-03 |
DOI: | 10.32614/CRAN.package.cacc |
Author: | Asier Moneva [aut, cre], Miriam Esteve [aut], Timothy C. Hart [aut] |
Maintainer: | Asier Moneva <amoneva at nscr.nl> |
BugReports: | https://github.com/amoneva/cacc/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/amoneva/cacc |
NeedsCompilation: | no |
Citation: | cacc citation info |
Materials: | README NEWS |
CRAN checks: | cacc results |
Reference manual: | cacc.pdf |
Package source: | cacc_0.1.1.tar.gz |
Windows binaries: | r-devel: cacc_0.1.1.zip, r-release: cacc_0.1.1.zip, r-oldrel: cacc_0.1.1.zip |
macOS binaries: | r-release (arm64): cacc_0.1.1.tgz, r-oldrel (arm64): cacc_0.1.1.tgz, r-release (x86_64): cacc_0.1.1.tgz, r-oldrel (x86_64): cacc_0.1.1.tgz |
Old sources: | cacc archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.