skillspace.approximation {CDM} | R Documentation |
Skill Space Approximation
Description
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).
Usage
skillspace.approximation(L, K, nmax=5000)
Arguments
L |
Number of skill classes used for approximation |
K |
Number of skills |
nmax |
Number of quasi-randomly generated skill classes using the |
Value
A matrix containing skill classes in rows
Note
This function uses the sfsmisc::QUnif
function from the sfsmisc
package.
References
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
See also gdina
(Example 9).
Examples
#############################################################################
# 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