Learn R Programming

⚠️There's a newer version (8.3-14) of this package.Take me there.

CDM (version 4.1)

Cognitive Diagnosis Modeling

Description

Functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous data. This package enables the estimation of the DINA and DINO model, the multiple group (polytomous) GDINA model, the multiple choice DINA model, the general diagnostic model (GDM), the multidimensional linear compensatory item response model and the structured latent class model (SLCA).

Copy Link

Version

Install

install.packages('CDM')

Monthly Downloads

6,939

Version

4.1

License

GPL (>= 2)

Maintainer

Alexander Robitzsch

Last Published

December 17th, 2014

Functions in CDM (4.1)

IRT.factor.scores

S3 Methods for Extracting Factor Scores (Person Classifications)

Helper Function for Conducting Likelihood Ratio Tests

Dataset for Polytomous GDINA Model

DTMR Fraction Data (Bradshaw et al., 2014)

Large-Scale Dataset with Multiple Groups

din.equivalent.class

Calculation of Equivalent Skill Classes in the DINA/DINO Model

Artificial Data: DINA and DINO

Several Datasets for the CDM Package

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

Extract Estimated Item Parameters and Skill Class Distribution Parameters

equivalent.dina

Determination of a Statistically Equivalent DINA Model

cdm.est.class.accuracy

Classification Reliability in a CDM

S3 Methods for Extracting Item Response Functions

ideal.response.pattern

Ideal Response Pattern

Cognitive Diagnosis Modeling: The RPackage CDM

personfit.appropriateness

Appropriateness Statistic for Person Fit Assessment

S3 Methods for Assessing Model Fit

din.deterministic

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

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

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

Fraction Subtraction Dataset 2

print.summary.din

Print Method for Objects of Class summary.din

Differential Item Functioning in the GDINA Model

S-X2 Item Fit Statistic for Dichotomous Data

din.validate.qmatrix

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

Summary Method for Objects of Class din

Information Criteria

data.timss07.G4.lee

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

Dataset SDA6 (Jurich & Bradshaw, 2014)

Asymptotic Covariance Matrix, Standard Errors and Confidence Intervals

Function for Estimating the Generalized DINA (GDINA) Model

fraction.subtraction.data

Fraction Subtraction Data

Simulation of the GDINA model

S3 Methods for Computing Item Fit

Parameter Estimation for Mixed DINA/DINO Model

Likelihood Ratio Test for Model Comparisons

Cognitive Diagnostic Indices based on Kullback-Leibler Information

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

Dataset Student Questionnaire

Dataset Jang (2009)

skillspace.hierarchy

Creation of a Hierarchical Skill Space

Plot Method for Objects of Class din

data.timss03.G8.su

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

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

Fraction Subtraction Dataset 1

General Diagnostic Model

fraction.subtraction.qmatrix

Fraction Subtraction Q-Matrix

Structured Latent Class Analysis (SLCA)

Tetrachoric or Polychoric Correlations between Attributes

skillspace.approximation

Skill Space Approximation

Multiple Choice DINA Model

Generalized Distance Discriminating Method

Extract Log-Likelihood

IRT.compareModels

Comparisons of Several Models

MELAB Data (Li, 2011)

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

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

sequential.items

Constructing a Dataset with Sequential Pseudo Items for Ordered Item Responses