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| GDINA-package | The Generalized DINA Model Framework |
| AIC.GDINA | Calibrate dichotomous and polytomous responses |
| anova.GDINA | Calibrate dichotomous and polytomous responses |
| att.structure | Generate hierarchical attribute structures |
| attributepattern | Generate all possible attribute patterns |
| autoGDINA | Q-matrix validation, model selection and calibration in one run |
| bdiagMatrix | Create a block diagonal matrix |
| BIC.GDINA | Calibrate dichotomous and polytomous responses |
| cjoint | Combine R Objects by Columns |
| ClassRate | Classification Rate Evaluation |
| designmatrix | Design matrix for parameter transformation |
| deviance.GDINA | Calibrate dichotomous and polytomous responses |
| dif | Differential item functioning for cognitive diagnosis models |
| ecpe | Examination for the Certificate of Proficiency in English (ECPE) data |
| extract | extract elements from objects of various classes |
| extract.GDINA | Calibrate dichotomous and polytomous responses |
| extract.itemfit | Item fit statistics |
| extract.modelcomp | Item-level model comparison using Wald test |
| extract.Qval | Q-matrix validation |
| extract.simGDINA | Data simulation based on the G-DINA models |
| frac20 | Tatsuoka's fraction subtraction data |
| GDINA | Calibrate dichotomous and polytomous responses |
| heatplot | Item fit plots |
| heatplot.itemfit | Item fit statistics |
| hoparm | extract higher-order parameters |
| hoparm.GDINA | Calibrate dichotomous and polytomous responses |
| indlogLik | Extract log-likelihood for each individual |
| indlogLik.GDINA | Calibrate dichotomous and polytomous responses |
| indlogPost | Extract log posterior for each individual |
| indlogPost.GDINA | Calibrate dichotomous and polytomous responses |
| itemfit | Item fit statistics |
| itemparm | extract lower-order structural (item) parameters |
| itemparm.GDINA | Calibrate dichotomous and polytomous responses |
| LC2LG | Transformation between latent classes and latent groups |
| logLik.GDINA | Calibrate dichotomous and polytomous responses |
| mesaplot | Mesa plot for Q-matrix validation |
| modelcomp | Item-level model comparison using Wald test |
| monocheck | This function checks if monotonicity is violated |
| npar | Calculate the number of parameters |
| npar.GDINA | Calibrate dichotomous and polytomous responses |
| personparm | calculate lower-order incidental (person) parameters |
| personparm.GDINA | Calibrate dichotomous and polytomous responses |
| plotIRF | Plot item success probability |
| Qval | Q-matrix validation |
| rowCount | Count and label unique rows in a data frame |
| rowMatch | Count the frequency of a row vector in a data frame |
| score | Score function |
| sim10GDINA | Simulated data, Q-matrix and item parameters (10 items, G-DINA model) |
| sim20seqGDINA | Simulated data, Q-matrix and item parameters (20 items, sequential DINA model) |
| sim21seqDINA | Simulated data and Qc-matrix based on the sequential DINA model |
| sim30DINA | Simulated data Q-matrix and item parameters (30 items, DINA model) |
| sim30GDINA | Simulated data, Q-matrix and item parameters (30 items, G-DINA model) |
| sim30pGDINA | Simulated data, Q-matrix and item parameters (30 items, polytomous G-DINA model) |
| simGDINA | Data simulation based on the G-DINA models |
| startGDINA | Graphical user interface of the GDINA function |
| summary.autoGDINA | Q-matrix validation, model selection and calibration in one run |
| summary.dif | Differential item functioning for cognitive diagnosis models |
| summary.GDINA | Calibrate dichotomous and polytomous responses |
| summary.itemfit | Item fit statistics |
| summary.modelcomp | Item-level model comparison using Wald test |
| summary.Qval | Q-matrix validation |
| unique_only | Unique values in a vector |
| unrestrQ | Generate unrestricted Qc matrix from an restricted Qc matrix |