Hidden Markov Cognitive Diagnosis Models for Learning

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Documentation for package ‘hmcdm’ version 2.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

hmcdm-package	hmcdm: Hidden Markov Cognitive Diagnosis Models for Learning
Design_array	Design array
ETAmat	Generate ideal response matrix
hmcdm	Gibbs sampler for learning models
inv_bijectionvector	Convert integer to attribute pattern
L_real_array	Observed response times array
OddsRatio	Compute item pairwise odds ratio
pp_check.hmcdm	Graphical posterior predictive checks for hidden Markov cognitive diagnosis model
print.summary.hmcdm	Summarizing Hidden Markov Cognitive Diagnosis Model Fits
Q_list_g	Generate a list of Q-matrices for each examinee.
Q_matrix	Q-matrix
random_Q	Generate random Q matrix
rOmega	Generate a random transition matrix for the first order hidden Markov model
sim_alphas	Generate attribute trajectories under the specified hidden Markov models
sim_hmcdm	Simulate responses from the specified model (entire cube)
sim_RT	Simulate item response times based on Wang et al.'s (2018) joint model of response times and accuracy in learning
summary.hmcdm	Summarizing Hidden Markov Cognitive Diagnosis Model Fits
Test_order	Test block ordering of each test version
Test_versions	Subjects' test version
TPmat	Generate monotonicity matrix
Y_real_array	Observed response accuracy array
_PACKAGE	hmcdm: Hidden Markov Cognitive Diagnosis Models for Learning