A set of psychometric tools for cognitive diagnosis modeling based on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) <DOI:10.1007/s11336-011-9207-7> and its extensions, including the sequential G-DINA model by Ma and de la Torre (2016) <DOI:10.1111/bmsp.12070> for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre <DOI:10.1177/0146621613479818> for polytomous attributes. Joint attribute distribution can be independent, saturated, higher-order, loglinear smoothed 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. For tutorials, please check Ma and de la Torre (2020) <DOI:10.18637/jss.v093.i14>, Ma and de la Torre (2019) <DOI:10.1111/emip.12262>, Ma (2019) <DOI:10.1007/978-3-030-05584-4_29> and de la Torre and Akbay (2019) <DOI:10.14689/ejer.2019.80.9>.

The Generalized DINA Model Framework

package-ubuntu-20.04-r-4.0.5#cran#GDINA-2.8.0

<table summary="R argblock"><tr valign="top">
<td><code>vec</code></td>
<td>
<p>a vector</p>
</td>
</tr></table>

<p><a href="../../base/html/unique.html">unique</a>
</p>

vec <- c(4,2,3,5,4,4,4)
unique_only(vec)
# see the difference from unique
unique(vec)

vec <- letters[1:5]
unique_only(vec)

package-ubuntu-20.04-r-4.0.5#cran#GDINA-2.8.0#docs#unique_only

unique_only

Description

Usage

Arguments

Value

See Also

Examples

GDINA

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