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hmcdm

The goal of hmcdm is to provide an implementation of Hidden Markov Cognitive Diagnosis Models for Learning.

Installation

You can install hmcdm from CRAN using:

install.packages("hmcdm")

Or, you can be on the cutting-edge development version on GitHub using:

if(!requireNamespace("remotes")) install.packages("remotes")
remotes::install_github("tmsalab/hmcdm")

Usage

To use hmcdm, load the package using:

library("hmcdm")

Authors

Susu Zhang, Shiyu Wang, Yinghan Chen, and Sunbeom Kwon

Citing the hmcdm package

To ensure future development of the package, please cite hmcdm package if used during an analysis or simulation study. Citation information for the package may be acquired by using in R:

citation("hmcdm")

License

GPL (>= 2)

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Version

Install

install.packages('hmcdm')

Monthly Downloads

419

Version

2.1.2

License

GPL (>= 2)

Issues

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Stars

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Maintainer

Sunbeom Kwon

Last Published

October 22nd, 2025

Functions in hmcdm (2.1.2)

L_real_array

Observed response times array
inv_bijectionvector

Convert integer to attribute pattern
pp_check.hmcdm

Graphical posterior predictive checks for hidden Markov cognitive diagnosis model
OddsRatio

Compute item pairwise odds ratio
sim_alphas

Generate attribute trajectories under the specified hidden Markov models
sim_RT

Simulate item response times based on Wang et al.'s (2018) joint model of response times and accuracy in learning
Design_array

Design array
random_Q

Generate random Q matrix
rOmega

Generate a random transition matrix for the first order hidden Markov model
ETAmat

Generate ideal response matrix
Y_real_array

Observed response accuracy array
TPmat

Generate monotonicity matrix
Q_list_g

Generate a list of Q-matrices for each examinee.
Test_versions

Subjects' test version
Q_matrix

Q-matrix
sim_hmcdm

Simulate responses from the specified model (entire cube)
print.summary.hmcdm

Summarizing Hidden Markov Cognitive Diagnosis Model Fits
hmcdm

Gibbs sampler for learning models
hmcdm-package

hmcdm: Hidden Markov Cognitive Diagnosis Models for Learning
Test_order

Test block ordering of each test version