Function reference • GDINA

All functions
`att.structure()`	Generate hierarchical attribute structures
`attributepattern()`	Generate all possible attribute patterns
`autoGDINA()` `summary(<autoGDINA>)`	Q-matrix validation, model selection and calibration in one run
`bdiagMatrix()`	Create a block diagonal matrix
`bootSE()`	Calculating standard errors and variance-covariance matrix using bootstrap methods
`CA()`	Calculate classification accuracy
`cjoint()`	Combine R Objects by Columns
`ClassRate()`	Classification Rate Evaluation
`designmatrix()`	Generate design matrix
`dif()` `summary(<dif>)`	Differential item functioning for cognitive diagnosis models
`DTM()`	Experimental function for diagnostic multiple-strategy CDMs
`ecpe`	Examination for the Certificate of Proficiency in English (ECPE) data
`extract()`	extract elements from objects of various classes
`frac20`	Tatsuoka's fraction subtraction data
`GDINA-package`	The Generalized DINA Model Framework
`GDINA()` `anova(<GDINA>)` `coef(<GDINA>)` `extract(<GDINA>)` `personparm(<GDINA>)` `logLik(<GDINA>)` `deviance(<GDINA>)` `nobs(<GDINA>)` `vcov(<GDINA>)` `npar(<GDINA>)` `indlogLik(<GDINA>)` `indlogPost(<GDINA>)` `summary(<GDINA>)`	CDM calibration under the G-DINA model framework
`GMSCDM()`	Estimating multiple-strategy cognitive diagnosis models
`ILCA()`	Iterative latent-class analysis
`indlogLik()`	Extract log-likelihood for each individual
`indlogPost()`	Extract log posterior for each individual
`itemfit()` `extract(<itemfit>)` `summary(<itemfit>)`	Item fit statistics
`itemparm()`	extract item parameters (deprecated)
`LC2LG()`	Transformation between latent classes and latent groups
`MCmodel()`	Multiple-choice models
`modelcomp()` `extract(<modelcomp>)` `summary(<modelcomp>)`	Item-level model comparison using Wald, LR or LM tests
`modelfit()`	Model fit statistics
`monocheck()`	This function checks if monotonicity is violated
`npar()`	Calculate the number of parameters
`personparm()`	calculate person (incidental) parameters
`plot(<GDINA>)`	Create plots for GDINA estimates
`plot(<itemfit>)`	Item fit plots
`plot(<Qval>)`	Mesa plot for Q-matrix validation
`Qval()` `extract(<Qval>)` `summary(<Qval>)`	Q-matrix validation
`rowMatch()`	Count the frequency of a row vector in a data frame
`score()`	Score function
`sim10GDINA`	Simulated data (10 items, G-DINA model)
`sim10MCDINA`	Simulated data (10 items, MC-DINA model)
`sim10MCDINA2`	Simulated data (10 items, MC-DINA model)
`sim20seqGDINA`	Simulated data (20 items, sequential G-DINA model)
`sim21seqDINA`	Simulated data (21 items, sequential DINA model)
`sim30DINA`	Simulated data (30 items, DINA model)
`sim30GDINA`	Simulated data (30 items, G-DINA model)
`sim30pGDINA`	Simulated data (30 items, polytomous G-DINA model)
`simDTM()`	Simulating data for diagnostic tree model
`simGDINA()` `extract(<simGDINA>)`	Data simulation based on the G-DINA models
`startGDINA()`	Graphical user interface of the GDINA function
`unique_only()`	Unique values in a vector
`unrestrQ()`	Generate unrestricted Qc matrix from an restricted Qc matrix

Reference

All functions