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CDM

Cognitive Diagnosis Modeling

If you use CDM and have suggestions for improvement or have found bugs, please email me at robitzsch@leibniz-ipn.de. Please always provide a minimal dataset, necessary to demonstrate the problem, a minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and all necessary information on the used librarys, the R version, and the OS it is run on, perhaps a sessionInfo().

Manual

The manual can be found here https://alexanderrobitzsch.github.io/CDM/

CRAN version

The official version of CDM is hosted on CRAN and can be found here. The CRAN version can be installed from within R using:

utils::install.packages("CDM")

GitHub version

The version hosted here is the development version of CDM. The GitHub version can be installed using devtools as:

devtools::install_github("alexanderrobitzsch/CDM")

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Version

Install

install.packages('CDM')

Monthly Downloads

3,247

Version

8.3-14

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/alexanderrobitzsch/CDM

Homepage

https://sites.google.com/view/alexander-robitzsch/software

Maintainer

Alexander Robitzsch

Last Published

July 13th, 2025

Functions in CDM (8.3-14)

S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior

Jackknifing an Item Response Model

IRT.marginal_posterior

S3 Method for Computation of Marginal Posterior Distribution

S3 Methods for Extracting Item Response Functions

IRT.parameterTable

S3 Method for Extracting a Parameter Table

S3 Methods for Computing Item Fit

S3 Methods for Assessing Model Fit

Cognitive Diagnostic Indices based on Kullback-Leibler Information

Wald Test for a Linear Hypothesis

cdm.est.class.accuracy

Classification Reliability in a CDM

Generation of a Replicate Design for IRT.jackknife

Dataset from Book 'Diagnostic Measurement' of Rupp, Templin and Henson (2010)

Extract Estimated Item Parameters and Skill Class Distribution Parameters

DTMR Fraction Data (Bradshaw et al., 2014)

Dataset Student Questionnaire

Several Datasets for the CDM Package

Likelihood Ratio Test for Model Comparisons

MELAB Data (Li, 2011)

Dataset for Polytomous GDINA Model

Dataset SDA6 (Jurich & Bradshaw, 2014)

Large-Scale Dataset with Multiple Groups

Dataset data.hr (Ravand et al., 2013)

Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matrices

data.timss03.G8.su

TIMSS 2003 Mathematics 8th Grade (Su et al., 2013)

PISA 2000 Reading Study (Chen & de la Torre, 2014)

Dataset Jang (2009)

din.deterministic

Deterministic Classification and Joint Maximum Likelihood Estimation of the Mixed DINA/DINO Model

din_identifiability

Identifiability Conditions of the DINA Model

Parameter Estimation for Mixed DINA/DINO Model

data.timss07.G4.lee

TIMSS 2007 Mathematics 4th Grade (Lee et al., 2011)

Test-specific and Item-specific Entropy for Latent Class Models

din.equivalent.class

Calculation of Equivalent Skill Classes in the DINA/DINO Model

Discrimination Indices at Item-Attribute, Item and Test Level

Variance Matrix of a Nonlinear Estimator Using the Delta Method

data.timss11.G4.AUT

TIMSS 2011 Mathematics 4th Grade Austrian Students

din.validate.qmatrix

Q-Matrix Validation (Q-Matrix Modification) for Mixed DINA/DINO Model

equivalent.dina

Determination of a Statistically Equivalent DINA Model

ideal.response.pattern

Ideal Response Pattern

fraction.subtraction.data

Fraction Subtraction Data

fraction.subtraction.qmatrix

Fraction Subtraction Q-Matrix

Generalized Distance Discriminating Method

Differential Item Functioning in the GDINA Model

General Diagnostic Model

eval_likelihood

Evaluation of Likelihood

Estimating the Generalized DINA (GDINA) Model

Wald Statistic for Item Fit of the DINA and ACDM Rule for GDINA Model

Create Dataset with Group-Specific Items

Multiple Choice DINA Model

Opens and Closes a sink Connection

numerical_Hessian

Numerical Computation of the Hessian Matrix

personfit.appropriateness

Appropriateness Statistic for Person Fit Assessment

Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations

Plot Method for Objects of Class din

Extract Log-Likelihood

S-X2 Item Fit Statistic for Dichotomous Data

Tetrachoric or Polychoric Correlations between Attributes

print.summary.din

Print Method for Objects of Class summary.din

skillspace.approximation

Skill Space Approximation

plot_item_mastery

S3 Methods for Plotting Item Probabilities

Simulate an Item Response Model

Simulation of the GDINA model

Regularized Latent Class Analysis

Summary Method for Objects of Class din

Asymptotic Covariance Matrix, Standard Errors and Confidence Intervals

skillspace.hierarchy

Creation of a Hierarchical Skill Space

Data Simulation Tool for DINA, DINO and mixed DINA and DINO Data

Prints summary and sink Output in a File

Expected Values and Predicted Probabilities from Item Response Response Models

sequential.items

Constructing a Dataset with Sequential Pseudo Items for Ordered Item Responses

Structured Latent Class Analysis (SLCA)

Artificial Data: DINA and DINO

Helper Function for Conducting Likelihood Ratio Tests

Utility Functions in CDM

IRT.expectedCounts

S3 Method for Extracting Expected Counts

S3 Method for Extracting Used Item Response Dataset

Individual Classification for Fitted Models

Information Criteria

IRT.compareModels

Comparisons of Several Models

Root Mean Square Deviation (RMSD) Item Fit Statistic

tools:::Rd_package_title("CDM")

IRT.frequencies

S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals

IRT.factor.scores

S3 Methods for Extracting Factor Scores (Person Classifications)

IRT.irfprobPlot

Plot Item Response Functions