Title: The Generalized DINA Model Framework
Authors@R: c(person(given = "Wenchao",family = "Ma", role = c("aut", "cre"),email = "wenchao.ma@rutgers.edu"),person(given = "Jimmy", family = "de la Torre", role = "aut"))
Description: A set of psychometric tools for cognitive diagnostic analyses for both dichotomous and polytomous responses. Various cognitive diagnosis models (CDMs) can be estimated, include the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) <DOI:10.1007/s11336-011-9207-7>, the sequential G-DINA model by Ma and de la Torre (2016)<DOI:10.1111/bmsp.12070>, and many other models they subsume. Joint attribute distribution can be saturated, higher-order or structured. Q-matrix validation, item and model fit statistics, model comparison at test and item level and differential item functioning can also be conducted. A graphical user interface is also provided.
Imports: stats, graphics, utils, Rcpp (>= 0.12.1), nloptr, MASS,
numDeriv, alabama, Rsolnp, ggplot2, shiny, shinydashboard
Collate: 'CR.R' 'GDI.R' 'GDINA-package.R' 'GDINA.R' 'HO.R'
'HOsupplement.R' 'M.R' 'M.mono.R' 'Mstep.R' 'Msupplement.R'
'autoGDINA.R' 'designmatrix.R' 'dif.R' 'ecpe.R' 'eta.loc.R'

Description: A set of psychometric tools for cognitive diagnostic analyses for
both dichotomous and polytomous responses. Various cognitive diagnosis models
can be estimated, include the generalized deterministic inputs, noisy
the sequential G-DINA model by Ma and de la Torre (2016) <DOI:10.1111/bmsp.12070>,
and many other models they subsume. Joint attribute distribution can
be saturated, higher-order or structured. Q-matrix validation, item and model
fit statistics, model comparison at test and item level and differential item
functioning can also be conducted. A graphical user interface is also provided.
Imports: alabama, data.table, graphics, ggplot2, MASS, nloptr,
numDeriv, Rcpp (>= 0.12.1), Rsolnp, stats, utils
Suggests: CDM, testthat, shiny, shinydashboard

Description: A set of psychometric tools for cognitive diagnostic analyses
for both dichotomous and polytomous responses. Various cognitive diagnosis
models can be estimated, include the generalized deterministic inputs, noisy