# Cognitive Diagnosis Modeling

## Documentation for package ‘CDM’ version 8.3-1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

A C D E F G I L M N O P R S V W

CDM-package | Cognitive Diagnosis Modeling

## -- A --

abs_approx | Utility Functions in 'CDM'
abs_approx_D1 | Utility Functions in 'CDM'
anova.din | Likelihood Ratio Test for Model Comparisons
anova.gdina | Likelihood Ratio Test for Model Comparisons
anova.gdm | Likelihood Ratio Test for Model Comparisons
anova.mcdina | Likelihood Ratio Test for Model Comparisons
anova.reglca | Likelihood Ratio Test for Model Comparisons
anova.slca | Likelihood Ratio Test for Model Comparisons

## -- C --

cat_paste | Utility Functions in 'CDM'
cdi.kli | Cognitive Diagnostic Indices based on Kullback-Leibler Information
CDM | Cognitive Diagnosis Modeling
CDM-utilities | Utility Functions in 'CDM'
cdm.est.class.accuracy | Classification Reliability in a CDM
cdm_attach_internal_function | Utility Functions in 'CDM'
cdm_calc_information_criteria | Utility Functions in 'CDM'
cdm_fa1 | Utility Functions in 'CDM'
cdm_fit_normal | Utility Functions in 'CDM'
cdm_matrix1 | Utility Functions in 'CDM'
cdm_matrix2 | Utility Functions in 'CDM'
cdm_matrixstring | Utility Functions in 'CDM'
cdm_parameter_regularization | Utility Functions in 'CDM'
cdm_pem_acceleration | Utility Functions in 'CDM'
cdm_pem_acceleration_assign_output_parameters | Utility Functions in 'CDM'
cdm_pem_inits | Utility Functions in 'CDM'
cdm_pem_inits_assign_parmlist | Utility Functions in 'CDM'
cdm_penalty_threshold_elnet | Utility Functions in 'CDM'
cdm_penalty_threshold_lasso | Utility Functions in 'CDM'
cdm_penalty_threshold_mcp | Utility Functions in 'CDM'
cdm_penalty_threshold_ridge | Utility Functions in 'CDM'
cdm_penalty_threshold_scad | Utility Functions in 'CDM'
cdm_penalty_threshold_scadL2 | Utility Functions in 'CDM'
cdm_penalty_threshold_tlp | Utility Functions in 'CDM'
cdm_penalty_values | Utility Functions in 'CDM'
cdm_print_summary_call | Utility Functions in 'CDM'
cdm_print_summary_computation_time | Utility Functions in 'CDM'
cdm_print_summary_data_frame | Utility Functions in 'CDM'
cdm_print_summary_information_criteria | Utility Functions in 'CDM'
CDM_rbind_fill | Utility Functions in 'CDM'
CDM_require_namespace | Utility Functions in 'CDM'
CDM_rmvnorm | Utility Functions in 'CDM'
coef.din | Extract Estimated Item Parameters and Skill Class Distribution Parameters
coef.gdina | Extract Estimated Item Parameters and Skill Class Distribution Parameters
coef.gdm | Extract Estimated Item Parameters and Skill Class Distribution Parameters
coef.IRT.jackknife | Jackknifing an Item Response Model
coef.mcdina | Extract Estimated Item Parameters and Skill Class Distribution Parameters
coef.slca | Extract Estimated Item Parameters and Skill Class Distribution Parameters
confint.din | Asymptotic Covariance Matrix, Standard Errors and Confidence Intervals
csink | Opens and Closes a 'sink' Connection

## -- D --

Data-sim | Artificial Data: DINA and DINO
data.cdm | Several Datasets for the 'CDM' Package
data.cdm01 | Several Datasets for the 'CDM' Package
data.cdm02 | Several Datasets for the 'CDM' Package
data.cdm03 | Several Datasets for the 'CDM' Package
data.cdm04 | Several Datasets for the 'CDM' Package
data.cdm05 | Several Datasets for the 'CDM' Package
data.cdm06 | Several Datasets for the 'CDM' Package
data.cdm07 | Several Datasets for the 'CDM' Package
data.cdm08 | Several Datasets for the 'CDM' Package
data.cdm09 | Several Datasets for the 'CDM' Package
data.cdm10 | Several Datasets for the 'CDM' Package
data.dcm | Dataset from Book 'Diagnostic Measurement' of Rupp, Templin and Henson (2010)
data.dtmr | DTMR Fraction Data (Bradshaw et al., 2014)
data.ecpe | Dataset ECPE
data.fraction | Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matrices
data.fraction1 | Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matrices
data.fraction2 | Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matrices
data.fraction3 | Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matrices
data.fraction4 | Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matrices
data.fraction5 | Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matrices
data.hr | Dataset 'data.hr' (Ravand et al., 2013)
data.jang | Dataset Jang (2009)
data.melab | MELAB Data (Li, 2011)
data.mg | Large-Scale Dataset with Multiple Groups
data.pgdina | Dataset for Polytomous GDINA Model
data.pisa00R.cc | PISA 2000 Reading Study (Chen & de la Torre, 2014)
data.pisa00R.ct | PISA 2000 Reading Study (Chen & de la Torre, 2014)
data.sda6 | Dataset SDA6 (Jurich & Bradshaw, 2014)
data.Students | Dataset Student Questionnaire
data.timss03.G8.su | TIMSS 2003 Mathematics 8th Grade (Su et al., 2013)
data.timss07.G4.lee | TIMSS 2007 Mathematics 4th Grade (Lee et al., 2011)
data.timss07.G4.py | TIMSS 2007 Mathematics 4th Grade (Lee et al., 2011)
data.timss07.G4.Qdomains | TIMSS 2007 Mathematics 4th Grade (Lee et al., 2011)
data.timss11.G4.AUT | TIMSS 2011 Mathematics 4th Grade Austrian Students
data.timss11.G4.AUT.part | TIMSS 2011 Mathematics 4th Grade Austrian Students
data.timss11.G4.sa | TIMSS 2011 Mathematics 4th Grade Austrian Students
deltaMethod | Variance Matrix of a Nonlinear Estimator Using the Delta Method
din | Parameter Estimation for Mixed DINA/DINO Model
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
din.validate.qmatrix | Q-Matrix Validation (Q-Matrix Modification) for Mixed DINA/DINO Model
din_identifiability | Identifiability Conditions of the DINA Model
discrim.index | Discrimination Indices at Item-Attribute, Item and Test Level
discrim.index.din | Discrimination Indices at Item-Attribute, Item and Test Level
discrim.index.gdina | Discrimination Indices at Item-Attribute, Item and Test Level
discrim.index.mcdina | Discrimination Indices at Item-Attribute, Item and Test Level

## -- E --

entropy.lca | Test-specific and Item-specific Entropy for Latent Class Models
equivalent.dina | Determination of a Statistically Equivalent DINA Model
eval_likelihood | Evaluation of Likelihood

## -- F --

fraction.subtraction.data | Fraction Subtraction Data
fraction.subtraction.qmatrix | Fraction Subtraction Q-Matrix

## -- G --

gdd | Generalized Distance Discriminating Method
gdina | Estimating the Generalized DINA (GDINA) Model
gdina.dif | Differential Item Functioning in the GDINA Model
gdina.wald | Wald Statistic for Item Fit of the DINA and ACDM Rule for GDINA Model
gdm | General Diagnostic Model

## -- I --

ideal.response.pattern | Ideal Response Pattern
IRT.anova | Helper Function for Conducting Likelihood Ratio Tests
IRT.classify | Individual Classification for Fitted Models
IRT.compareModels | Comparisons of Several Models
IRT.data | S3 Method for Extracting Used Item Response Dataset
IRT.data.din | S3 Method for Extracting Used Item Response Dataset
IRT.data.gdina | S3 Method for Extracting Used Item Response Dataset
IRT.data.gdm | S3 Method for Extracting Used Item Response Dataset
IRT.data.mcdina | S3 Method for Extracting Used Item Response Dataset
IRT.data.reglca | S3 Method for Extracting Used Item Response Dataset
IRT.data.slca | S3 Method for Extracting Used Item Response Dataset
IRT.derivedParameters | Jackknifing an Item Response Model
IRT.expectedCounts | S3 Method for Extracting Expected Counts
IRT.expectedCounts.din | S3 Method for Extracting Expected Counts
IRT.expectedCounts.gdina | S3 Method for Extracting Expected Counts
IRT.expectedCounts.gdm | S3 Method for Extracting Expected Counts
IRT.expectedCounts.mcdina | S3 Method for Extracting Expected Counts
IRT.expectedCounts.reglca | S3 Method for Extracting Expected Counts
IRT.expectedCounts.slca | S3 Method for Extracting Expected Counts
IRT.factor.scores | S3 Methods for Extracting Factor Scores (Person Classifications)
IRT.factor.scores.din | S3 Methods for Extracting Factor Scores (Person Classifications)
IRT.factor.scores.gdina | S3 Methods for Extracting Factor Scores (Person Classifications)
IRT.factor.scores.gdm | S3 Methods for Extracting Factor Scores (Person Classifications)
IRT.factor.scores.mcdina | S3 Methods for Extracting Factor Scores (Person Classifications)
IRT.factor.scores.slca | S3 Methods for Extracting Factor Scores (Person Classifications)
IRT.frequencies | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT.frequencies.din | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT.frequencies.gdina | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT.frequencies.gdm | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT.frequencies.mcdina | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT.frequencies.slca | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT.IC | Information Criteria
IRT.irfprob | S3 Methods for Extracting Item Response Functions
IRT.irfprob.din | S3 Methods for Extracting Item Response Functions
IRT.irfprob.gdina | S3 Methods for Extracting Item Response Functions
IRT.irfprob.gdm | S3 Methods for Extracting Item Response Functions
IRT.irfprob.mcdina | S3 Methods for Extracting Item Response Functions
IRT.irfprob.reglca | S3 Methods for Extracting Item Response Functions
IRT.irfprob.slca | S3 Methods for Extracting Item Response Functions
IRT.irfprobPlot | Plot Item Response Functions
IRT.itemfit | S3 Methods for Computing Item Fit
IRT.itemfit.din | S3 Methods for Computing Item Fit
IRT.itemfit.gdina | S3 Methods for Computing Item Fit
IRT.itemfit.gdm | S3 Methods for Computing Item Fit
IRT.itemfit.reglca | S3 Methods for Computing Item Fit
IRT.itemfit.slca | S3 Methods for Computing Item Fit
IRT.jackknife | Jackknifing an Item Response Model
IRT.jackknife.gdina | Jackknifing an Item Response Model
IRT.likelihood | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.likelihood.din | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.likelihood.gdina | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.likelihood.gdm | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.likelihood.mcdina | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.likelihood.reglca | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.likelihood.slca | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.marginal_posterior | S3 Method for Computation of Marginal Posterior Distribution
IRT.marginal_posterior.din | S3 Method for Computation of Marginal Posterior Distribution
IRT.marginal_posterior.gdina | S3 Method for Computation of Marginal Posterior Distribution
IRT.marginal_posterior.mcdina | S3 Method for Computation of Marginal Posterior Distribution
IRT.modelfit | S3 Methods for Assessing Model Fit
IRT.modelfit.din | S3 Methods for Assessing Model Fit
IRT.modelfit.gdina | S3 Methods for Assessing Model Fit
IRT.parameterTable | S3 Method for Extracting a Parameter Table
IRT.posterior | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.posterior.din | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.posterior.gdina | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.posterior.gdm | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.posterior.mcdina | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.posterior.reglca | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.posterior.slca | S3 Methods for Extracting of the Individual Likelihood and the Individual Posterior
IRT.predict | Expected Values and Predicted Probabilities from Item Response Response Models
IRT.repDesign | Generation of a Replicate Design for 'IRT.jackknife'
IRT.RMSD | Root Mean Square Deviation (RMSD) Item Fit Statistic
IRT.se | Asymptotic Covariance Matrix, Standard Errors and Confidence Intervals
IRT.se.din | Asymptotic Covariance Matrix, Standard Errors and Confidence Intervals
IRT_frequencies_default | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT_frequencies_wrapper | S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate Marginals
IRT_RMSD_calc_rmsd | Root Mean Square Deviation (RMSD) Item Fit Statistic
itemfit.rmsea | RMSEA Item Fit
itemfit.sx2 | S-X2 Item Fit Statistic for Dichotomous Data
item_by_group | Create Dataset with Group-Specific Items

## -- L --

logLik.din | Extract Log-Likelihood
logLik.gdina | Extract Log-Likelihood
logLik.gdm | Extract Log-Likelihood
logLik.mcdina | Extract Log-Likelihood
logLik.reglca | Extract Log-Likelihood
logLik.slca | Extract Log-Likelihood

## -- M --

mcdina | Multiple Choice DINA Model
modelfit.cor | Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations
modelfit.cor.din | Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations
modelfit.cor2 | Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations

## -- N --

numerical_gradient | Numerical Computation of the Hessian Matrix
numerical_Hessian | Numerical Computation of the Hessian Matrix
numerical_Hessian_partial | Numerical Computation of the Hessian Matrix

## -- O --

osink | Opens and Closes a 'sink' Connection

## -- P --

personfit.appropriateness | Appropriateness Statistic for Person Fit Assessment
plot.din | Plot Method for Objects of Class din
plot.gdina | Estimating the Generalized DINA (GDINA) Model
plot.gdm | General Diagnostic Model
plot.itemfit.sx2 | S-X2 Item Fit Statistic for Dichotomous Data
plot.personfit.appropriateness | Appropriateness Statistic for Person Fit Assessment
plot.slca | Structured Latent Class Analysis (SLCA)
plot_item_mastery | S3 Methods for Plotting Item Probabilities
plot_item_mastery.din | S3 Methods for Plotting Item Probabilities
plot_item_mastery.gdina | S3 Methods for Plotting Item Probabilities
predict.din | Expected Values and Predicted Probabilities from Item Response Response Models
predict.gdina | Expected Values and Predicted Probabilities from Item Response Response Models
predict.gdm | Expected Values and Predicted Probabilities from Item Response Response Models
predict.mcdina | Expected Values and Predicted Probabilities from Item Response Response Models
predict.slca | Expected Values and Predicted Probabilities from Item Response Response Models
prep_data_long_format | Evaluation of Likelihood
print.din | Parameter Estimation for Mixed DINA/DINO Model
print.gdina | Estimating the Generalized DINA (GDINA) Model
print.gdm | General Diagnostic Model
print.mcdina | Multiple Choice DINA Model
print.slca | Structured Latent Class Analysis (SLCA)
print.summary.din | Print Method for Objects of Class summary.din

## -- R --

reglca | Regularized Latent Class Analysis

## -- S --

sequential.items | Constructing a Dataset with Sequential Pseudo Items for Ordered Item Responses
sim.din | Data Simulation Tool for DINA, DINO and mixed DINA and DINO Data
sim.dina | Artificial Data: DINA and DINO
sim.dino | Artificial Data: DINA and DINO
sim.gdina | Simulation of the GDINA model
sim.gdina.prepare | Simulation of the GDINA model
sim.qmatrix | Artificial Data: DINA and DINO
sim_model | Simulate an Item Response Model
skill.cor | Tetrachoric or Polychoric Correlations between Attributes
skill.polychor | Tetrachoric or Polychoric Correlations between Attributes
skillspace.approximation | Skill Space Approximation
skillspace.full | Creation of a Hierarchical Skill Space
skillspace.hierarchy | Creation of a Hierarchical Skill Space
slca | Structured Latent Class Analysis (SLCA)
summary.cdi.kli | Cognitive Diagnostic Indices based on Kullback-Leibler Information
summary.din | Summary Method for Objects of Class din
summary.din_identifiability | Identifiability Conditions of the DINA Model
summary.discrim.index | Discrimination Indices at Item-Attribute, Item and Test Level
summary.entropy.lca | Test-specific and Item-specific Entropy for Latent Class Models
summary.gdina | Estimating the Generalized DINA (GDINA) Model
summary.gdina.dif | Differential Item Functioning in the GDINA Model
summary.gdina.wald | Wald Statistic for Item Fit of the DINA and ACDM Rule for GDINA Model
summary.gdm | General Diagnostic Model
summary.IRT.compareModels | Comparisons of Several Models
summary.IRT.modelfit.din | S3 Methods for Assessing Model Fit
summary.IRT.modelfit.gdina | S3 Methods for Assessing Model Fit
summary.IRT.RMSD | Root Mean Square Deviation (RMSD) Item Fit Statistic
summary.itemfit.sx2 | S-X2 Item Fit Statistic for Dichotomous Data
summary.mcdina | Multiple Choice DINA Model
summary.modelfit.cor.din | Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlations
summary.personfit.appropriateness | Appropriateness Statistic for Person Fit Assessment
summary.reglca | Regularized Latent Class Analysis
summary.slca | Structured Latent Class Analysis (SLCA)
summary_sink | Prints 'summary' and 'sink' Output in a File

## -- V --

vcov.din | Asymptotic Covariance Matrix, Standard Errors and Confidence Intervals
vcov.IRT.jackknife | Jackknifing an Item Response Model

## -- W --

WaldTest | Wald Test for a Linear Hypothesis