Nonparametric Methods for Cognitive Diagnosis
Maximum likelihood estimation of attribute profile
Nonparametric estimation of attribute profiles
Log-likelihood for cognitive diagnostic models
Probability of correct response for cognitive diagnostic models
Compute item fit statistics for outputs generated by estimation functi...
Joint maximum likelihood estimation of item parameters and examinee at...
Compute overall model fit statistics for outputs generated by estimati...
NPCD: The Package for Nonparametric Methods for Cognitive Diagnosis
Maximum likelihood estimation of item parameters for cognitive diagnos...
Produce diagnostic plots
Print outputs generated from the functions in the package.
Refine the Q-matrix by minimizing the residual sum of square (RSS)
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.