mirt (version 1.35.1)

traditional2mirt: Convert traditional IRT metric into slope-intercept form used in mirt

Description

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.

Usage

traditional2mirt(x, cls, ncat)

Arguments

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

Value

a named vector of slope-intercept parameters (if supported)

Details

Supported class transformations for the cls input are:

Rasch, 2PL, 3PL, 3PLu, 4PL

Form must be: (discrimination, difficulty, lower-bound, upper-bound)

graded

Form must be: (discrimination, difficulty 1, difficulty 2, ..., difficulty k-1)

gpcm

Form must be: (discrimination, difficulty 1, difficulty 2, ..., difficulty k-1)

nominal

Form must be: (discrimination 1, discrimination 2, ..., discrimination k, difficulty 1, difficulty 2, ..., difficulty k)

Examples

# NOT RUN {
# 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


# }