Package: MRCV 0.4-0
Chris Bilder
MRCV: Methods for Analyzing Multiple Response Categorical Variables (MRCVs)
Provides functions for analyzing the association between one single response categorical variable (SRCV) and one multiple response categorical variable (MRCV), or between two or three MRCVs. A modified Pearson chi-square statistic can be used to test for marginal independence for the one or two MRCV case, or a more general loglinear modeling approach can be used to examine various other structures of association for the two or three MRCV case. Bootstrap- and asymptotic-based standardized residuals and model-predicted odds ratios are available, in addition to other descriptive information. Statisical methods implemented are described in Bilder et al. (2000) <doi:10.1080/03610910008813665>, Bilder and Loughin (2004) <doi:10.1111/j.0006-341X.2004.00147.x>, Bilder and Loughin (2007) <doi:10.1080/03610920600974419>, and Koziol and Bilder (2014) <https://journal.r-project.org/articles/RJ-2014-014/>.
Authors:
MRCV_0.4-0.tar.gz
MRCV_0.4-0.tar.gz(r-4.5-noble)MRCV_0.4-0.tar.gz(r-4.4-noble)
MRCV_0.4-0.tgz(r-4.4-emscripten)MRCV_0.3-3.tgz(r-4.3-emscripten)
MRCV.pdf |MRCV.html✨
MRCV/json (API)
| # Install 'MRCV' in R: |
| install.packages('MRCV', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:51f5842ad3. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 22 2024 |
| R-4.5-linux | OK | Dec 22 2024 |
Exports:genloglinitem.response.tablemarginal.tableMI.statMI.test
Dependencies:base64encdigestevaluatefastmaphighrhtmltoolsknitrrlangtablesxfunyaml
