drm: Dichotomous Response Model (DRM) Probabilities

In irtQ: Unidimensional Item Response Theory Modeling

Dichotomous Response Model (DRM) Probabilities

Description

This function computes the probability of correct answers for multiple items for a given set of theta values using the IRT 1PL, 2PL, and 3PL models.

Usage

drm(theta, a, b, g = NULL, D = 1)

Arguments

theta	A vector of ability values.
a	A vector of item discrimination (or slope) parameters.
b	A vector of item difficulty (or threshold) parameters.
g	A vector of item guessing parameters.
D	A scaling factor in IRT models to make the logistic function as close as possible to the normal ogive function (if set to 1.7). Default is 1.

Details

g does not need to be specified when the response probabilities of the 1PL and 2PL models are computed.

Value

This function returns a matrix where a row indicates the ability and a column represents the item.

Author(s)

Hwanggyu Lim [e-mail]

See Also

prm

Examples

## when vectors are used for both theta values and item parameters (3PLM)
drm(c(-0.1, 0.0, 1.5), a = c(1, 2), b = c(0, 1), g = c(0.2, 0.1), D = 1)

## when vectors are only used for item parameters (2PLM)
drm(0.0, a = c(1, 2), b = c(0, 1), D = 1)

## when vectors are only used for theta values (3PLM)
drm(c(-0.1, 0.0, 1.5), a = 1, b = 1, g = 0.2, D = 1)

irtQ documentation built on Sept. 11, 2024, 5:10 p.m.