Author: Yi Zheng (University of Illinois at Urbana-Champaign) and
Chia-Yi Chiu (Rutgers, the State University of New Jersey),
with contributions from Jeffrey A. Douglas (University of

Authors@R: c(person("Yi", "Zheng", role = c("aut", "cre"),
person("Chia-Yi", "Chiu", role = "aut"))
Author: Yi Zheng (University of Illinois at Urbana-Champaign) and Chia-Yi Chiu (Rutgers, the State University of New Jersey), with contributions from Jeffrey A. Douglas (University of Illinois at Urbana-Champaign)
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.

Authors@R: c(person("Yi", "Zheng", role = c("aut", "cre"), email = "yizheng1@illinois.edu"), person("Chia-Yi", "Chiu", role = "aut"), person("Jeffrey A.", "Douglas", role = "ctb", email = "jeffdoug@illinois.edu"))
Author: Yi Zheng [aut, cre], Chia-Yi Chiu [aut], Jeffrey A. Douglas [ctb]
Description: This package performs 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.