Convert traditional IRT metric into slope-intercept form used in mirt
This is a helper function for users who have previously available traditional/classical
IRT parameters and want to know the equivalent slope-intercept translation used in mirt.
Note that this function assumes that the supplied models are unidimensional by definition (i.e.,
will have only one slope/discrimination). If there is no supported slope-interecept transformation
available then the original vector of parameters will be returned by default.
traditional2mirt(x, cls, ncat)
x |
a vector of parameters to tranform |
cls |
the class or itemtype of the supplied model |
ncat |
the number of categories implied by the IRT model |
Supported class transformations for the cls input are:
Form must be: (discrimination, difficulty, lower-bound, upper-bound)
Form must be: (discrimination, difficulty 1, difficulty 2, ..., difficulty k-1)
Form must be: (discrimination, difficulty 1, difficulty 2, ..., difficulty k-1)
Form must be: (discrimination 1, discrimination 2, ..., discrimination k, difficulty 1, difficulty 2, ..., difficulty k)
a named vector of slope-intercept parameters (if supported)
# classical 3PL model vec <- c(a=1.5, b=-1, g=.1, u=1) slopeint <- traditional2mirt(vec, '3PL', ncat=2) slopeint # classical graded model (four category) vec <- c(a=1.5, b1=-1, b2=0, b3=1.5) slopeint <- traditional2mirt(vec, 'graded', ncat=4) slopeint # classical generalize partial credit model (four category) vec <- c(a=1.5, b1=-1, b2=0, b3=1.5) slopeint <- traditional2mirt(vec, 'gpcm', ncat=4) slopeint # classical nominal model (4 category) vec <- c(a1=.5, a2 = -1, a3=1, a4=-.5, d1=1, d2=-1, d3=-.5, d4=.5) slopeint <- traditional2mirt(vec, 'nominal', ncat=4) slopeint
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