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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("ccrs")

0.1.0 by Mariko Takagishi, 22 days ago


Browse source code at https://github.com/cran/ccrs


Authors: Mariko Takagishi [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports cds, colorspace, dplyr, graphics, limSolve, lsbclust, methods, msm, parallel, stats, utils


See at CRAN