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 |
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 |
macOS binaries: | r-release: ccrs_0.1.0.tgz, r-oldrel: ccrs_0.1.0.tgz |
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