Package: ccrs 0.1.0

Mariko Takagishi

ccrs: Correct and Cluster Response Style Biased Data

Functions for performing Correcting and Clustering response-style-biased preference data (CCRS). The main functions are correct.RS() for correcting for response styles, and ccrs() for simultaneously correcting and content-based clustering. The procedure begin with making rank-ordered boundary data from the given preference matrix using a function called create.ccrsdata(). Then in correct.RS(), the response style is corrected as follows: the rank-ordered boundary data are smoothed by I-spline functions, the given preference data are transformed by the smoothed functions. The resulting data matrix, which is considered as bias-corrected data, can be used for any data analysis methods. If one wants to cluster respondents based on their indicated preferences (content-based clustering), ccrs() can be applied to the given (response-style-biased) preference data, which simultaneously corrects for response styles and clusters respondents based on the contents. Also, the correction result can be checked by plot.crs() function.

Authors:Mariko Takagishi [aut, cre]

ccrs_0.1.0.tar.gz
ccrs_0.1.0.tar.gz(r-4.5-noble)ccrs_0.1.0.tar.gz(r-4.4-noble)
ccrs_0.1.0.tgz(r-4.4-emscripten)ccrs_0.1.0.tgz(r-4.3-emscripten)
ccrs.pdf |ccrs.html✨
ccrs/json (API)

# Install 'ccrs' in R:
install.packages('ccrs', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 193 downloads 6 exports 59 dependencies

Last updated 6 years agofrom:3f94efe42a. Checks:1 OK, 2 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 14 2025
R-4.5-linuxNOTEMar 14 2025
R-4.4-linuxNOTEMar 14 2025

Exports:ccrsconvert.X2Fcorrect.rscreate.ccrsdatagenerate.rsdatatransformRSdata

Dependencies:ADGofTestcdscliclueclustercodetoolscolorspacecopuladoParalleldplyrexpmfansifarverforeachgenericsggplot2gluegridExtragslgtableisobanditeratorslabelinglatticelifecyclelimSolvelpSolvelsbclustmagrittrMASSMatrixmgcvmsmmunsellmvtnormnlmenumDerivpcaPPpillarpkgconfigplyrpsplinequadprogR6RColorBrewerRcppreshape2rlangscalesstablediststringistringrsurvivaltibbletidyselectutf8vctrsviridisLitewithr

Citation

To cite package ‘ccrs’ in publications use:

Takagishi M (2019). ccrs: Correct and Cluster Response Style Biased Data. R package version 0.1.0, https://CRAN.R-project.org/package=ccrs.

Corresponding BibTeX entry: 

  @Manual{,
    title = {ccrs: Correct and Cluster Response Style Biased Data},
    author = {Mariko Takagishi},
    year = {2019},
    note = {R package version 0.1.0},
    url = {https://CRAN.R-project.org/package=ccrs},
  }