Functions for cognitive diagnosis modeling and multidimensional item response modeling
for dichotomous and polytomous item responses. This package enables the estimation of
the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>),
the multiple group (polytomous) GDINA model (de la Torre, 2011,
<doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009,
<doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008,
<doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992,
<doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis
(Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>).
See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02>
for further details on estimation and the package structure.
For tutorials on how to use the CDM package see
George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as
Ravand and Robitzsch (2015).

Functions for cognitive diagnosis modeling and multidimensional item response modeling
for dichotomous and polytomous item responses. This package enables the estimation of
the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>),
the multiple group (polytomous) GDINA model (de la Torre, 2011,
<doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009,
<doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008,
<doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992,
<doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis
(Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>).
See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02>
for further details on estimation and the package structure.
For tutorials on how to use the CDM package see
George and Robitzsch (2015) as well as
Ravand and Robitzsch (2015).

BIFIEsurvey, GDINA, lattice, miceadds, mirt, ROI, sirt, TAM