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.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: cds, colorspace, dplyr, graphics, limSolve, lsbclust, methods, msm, parallel, stats, utils
Published: 2019-03-04
Author: Mariko Takagishi [aut, cre]
Maintainer: Mariko Takagishi <m.takagishi0728 at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: ccrs results

Downloads:

Reference manual: ccrs.pdf
Package source: ccrs_0.1.0.tar.gz
Windows binaries: r-devel: ccrs_0.1.0.zip, r-release: ccrs_0.1.0.zip, r-oldrel: ccrs_0.1.0.zip
OS X binaries: r-release: ccrs_0.1.0.tgz, r-oldrel: ccrs_0.1.0.tgz

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