Nonparametric Item Response Theory

Fits nonparametric item and option characteristic curves using kernel smoothing. It allows for optimal selection of the smoothing bandwidth using cross-validation and a variety of exploratory plotting tools. The kernel smoothing is based on methods described in Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.


Reference manual

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install.packages("KernSmoothIRT")

6.6 by Brian McGuire, 3 months ago


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


Authors: Angelo Mazza [aut] , Antonio Punzo [aut] , Brian McGuire [aut, cre]


Documentation:   PDF Manual  


GPL-2 license


Imports Rcpp, plotrix, rgl, methods

Linking to Rcpp


See at CRAN