KernSmoothIRT: 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.

Package details

AuthorAngelo Mazza, Antonio Punzo, Brian McGuire
MaintainerBrian McGuire <mcguirebc@gmail.com>
LicenseGPL-2
Version6.4
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("KernSmoothIRT")

Try the KernSmoothIRT package in your browser

Any scripts or data that you put into this service are public.

KernSmoothIRT documentation built on March 26, 2020, 7:42 p.m.