Package: NPCD
Type: Package
Version: 1.0-1
Date: 2012-12-21
Title: Nonparametric Methods for Cognitive Diagnosis
Authors@R: c(person("Yi", "Zheng", role = c("aut", "cre"), email =
"yizheng1@illinois.edu"), person("Chia-Yi", "Chiu", role =
"aut"))
Author: Yi Zheng (U of Illinois at Urbana-Champaign) and Chia-Yi Chiu
(Rutgers, the State U of New Jersey), with contributions from
Jeffrey A. Douglas (U of Illinois at Urbana-Champaign)
Maintainer: Yi Zheng <yizheng1@illinois.edu>
Description: This package performs an array of nonparametric estimation
methods for cognitive diagnostic models, including
nonparametric estimation of examinee attribute profiles, joint
maximum likelihood estimation of examinee attribute profiles
and item parameters, and nonparametric refinement of the
Q-matrix, as well as parametric algorithms such as maximum
likelihood estimation of examinee attribute profiles given item
parameters and maximum likelihood estimation of item parameters
given examinee attribute profiles.
Depends: R (>= 2.14.2), BB, R.oo
LazyLoad: yes
LazyData: yes
License: LGPL (>= 2.1)
Repository: CRAN
Packaged: 2013-02-04 23:55:27 UTC; Isabelle
Date/Publication: 2013-02-05 05:45:06

Authors@R: c(person("Yi", "Zheng", role = c("aut", "cre"), email = "yi.isabel.zheng@asu.edu"), person("Chia-Yi", "Chiu", role = "aut"), person("Jeffrey A.", "Douglas", role = "ctb", email = "jeffdoug@illinois.edu"))
Description: An array of nonparametric and parametric estimation methods for cognitive diagnostic models, including nonparametric classification of examinee attribute profiles, joint maximum likelihood estimation (JMLE) of examinee attribute profiles and item parameters, and nonparametric refinement of the Q-matrix, as well as conditional maximum likelihood estimation (CMLE) of examinee attribute profiles given item parameters and CMLE of item parameters given examinee attribute profiles. Currently the nonparametric methods in the package support both conjunctive and disjunctive models, and the parametric methods in the package support the DINA model, the DINO model, the NIDA model, the G-NIDA model, and the R-RUM model.