Skill Space Approximation
This function approximates the skill space with K skills to approximate a (typically high-dimensional) skill space of 2^K classes by L classes (L < 2^K). The large number of latent classes are represented by underlying continuous latent variables for the dichotomous skills (see George & Robitzsch, 2014, for more details).
skillspace.approximation(L, K, nmax=5000)
L |
Number of skill classes used for approximation |
K |
Number of skills |
nmax |
Number of quasi-randomly generated skill classes using the |
A matrix containing skill classes in rows
This function uses the sfsmisc::QUnif function from the sfsmisc
package.
George, A. C., & Robitzsch, A. (2014). Multiple group cognitive diagnosis models, with an emphasis on differential item functioning. Psychological Test and Assessment Modeling, 56(4), 405-432.
See also gdina (Example 9).
############################################################################# # EXAMPLE 1: Approximate a skill space of K=8 eight skills by 20 classes ############################################################################# #=> 2^8=256 latent classes if all latent classes would be used CDM::skillspace.approximation( L=20, K=8 ) ## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] ## P00000000 0 0 0 0 0 0 0 0 ## P00000001 0 0 0 0 0 0 0 1 ## P00001011 0 0 0 0 1 0 1 1 ## P00010011 0 0 0 1 0 0 1 1 ## P00101001 0 0 1 0 1 0 0 1 ## [...] ## P11011110 1 1 0 1 1 1 1 0 ## P11100110 1 1 1 0 0 1 1 0 ## P11111111 1 1 1 1 1 1 1 1
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