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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 may be found here https://alexanderrobitzsch.github.io/CDM/

CRAN version

The official version of CDM is hosted on CRAN and may 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

3,441

Version

8.2-6

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/alexanderrobitzsch/CDM

Homepage

https://sites.google.com/site/alexanderrobitzsch2/software

Maintainer

Alexander Robitzsch

Last Published

August 25th, 2022

Functions in CDM (8.2-6)

Information Criteria

IRT.compareModels

Comparisons of Several Models

IRT.expectedCounts

S3 Method for Extracting Expected Counts

Helper Function for Conducting Likelihood Ratio Tests

tools:::Rd_package_title("CDM")

S3 Method for Extracting Used Item Response Dataset

Utility Functions in CDM

IRT.frequencies

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

IRT.irfprobPlot

Plot Item Response Functions

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

S3 Methods for Computing Item Fit

IRT.parameterTable

S3 Method for Extracting a Parameter Table

Jackknifing an Item Response Model

Artificial Data: DINA and DINO

Individual Classification for Fitted Models

Dataset Student Questionnaire

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

Several Datasets for the CDM Package

Wald Test for a Linear Hypothesis

Generation of a Replicate Design for IRT.jackknife

Likelihood Ratio Test for Model Comparisons

cdm.est.class.accuracy

Classification Reliability in a CDM

Dataset SDA6 (Jurich & Bradshaw, 2014)

IRT.factor.scores

S3 Methods for Extracting Factor Scores (Person Classifications)

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

S3 Methods for Assessing Model Fit

IRT.marginal_posterior

S3 Method for Computation of Marginal Posterior Distribution

S3 Methods for Extracting Item Response Functions

MELAB Data (Li, 2011)

Large-Scale Dataset with Multiple Groups

DTMR Fraction Data (Bradshaw et al., 2014)

Cognitive Diagnostic Indices based on Kullback-Leibler Information

Dataset for Polytomous GDINA Model

Extract Estimated Item Parameters and Skill Class Distribution Parameters

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

Dataset Jang (2009)

data.timss03.G8.su

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

din_identifiability

Identifiability Conditions of the DINA Model

Discrimination Indices at Item-Attribute, Item and Test Level

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

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

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

Differential Item Functioning in the GDINA Model

Parameter Estimation for Mixed DINA/DINO Model

Variance Matrix of a Nonlinear Estimator Using the Delta Method

din.validate.qmatrix

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

Create Dataset with Group-Specific Items

equivalent.dina

Determination of a Statistically Equivalent DINA Model

Extract Log-Likelihood

fraction.subtraction.data

Fraction Subtraction Data

fraction.subtraction.qmatrix

Fraction Subtraction Q-Matrix

din.deterministic

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

din.equivalent.class

Calculation of Equivalent Skill Classes in the DINA/DINO Model

eval_likelihood

Evaluation of Likelihood

data.timss07.G4.lee

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

S-X2 Item Fit Statistic for Dichotomous Data

Estimating the Generalized DINA (GDINA) Model

Expected Values and Predicted Probabilities from Item Response Response Models

plot_item_mastery

S3 Methods for Plotting Item Probabilities

data.timss11.G4.AUT

TIMSS 2011 Mathematics 4th Grade Austrian Students

Simulation of the GDINA model

Plot Method for Objects of Class din

General Diagnostic Model

Generalized Distance Discriminating Method

numerical_Hessian

Numerical Computation of the Hessian Matrix

ideal.response.pattern

Ideal Response Pattern

personfit.appropriateness

Appropriateness Statistic for Person Fit Assessment

print.summary.din

Print Method for Objects of Class summary.din

Simulate an Item Response Model

Prints summary and sink Output in a File

Summary Method for Objects of Class din

Opens and Closes a sink Connection

Asymptotic Covariance Matrix, Standard Errors and Confidence Intervals

skillspace.approximation

Skill Space Approximation

Tetrachoric or Polychoric Correlations between Attributes

Multiple Choice DINA Model

sequential.items

Constructing a Dataset with Sequential Pseudo Items for Ordered Item Responses

skillspace.hierarchy

Creation of a Hierarchical Skill Space

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

Structured Latent Class Analysis (SLCA)

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

Regularized Latent Class Analysis

Root Mean Square Deviation (RMSD) Item Fit Statistic