irtQ (version 1.0.0)

drm: Dichotomous Response Model (DRM) Probabilities

Description

This function computes the probability of a correct response for multiple items given a set of theta values using the 1PL, 2PL, or 3PL item response models.

Usage

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

Value

A matrix of response probabilities, where rows represent ability values (theta) and columns represent items.

Arguments

theta

A numeric vector of ability values (latent traits).

a

A numeric vector of item discrimination (slope) parameters.

b

A numeric vector of item difficulty parameters.

g

A numeric vector of item guessing parameters. Not required for 1PL or 2PL models.

D

A scaling constant used in IRT models to make the logistic function closely approximate the normal ogive function. A value of 1.7 is commonly used for this purpose. Default is 1.

Author

Hwanggyu Lim

Details

If g is not specified, the function assumes a guessing parameter of 0 for all items, corresponding to the 1PL or 2PL model. The function automatically adjusts the model form based on the presence of g.

See Also

prm()

Examples

## Example 1: theta and item parameters for 3PL model
drm(c(-0.1, 0.0, 1.5), a = c(1, 2), b = c(0, 1), g = c(0.2, 0.1), D = 1)

## Example 2: single theta value with 2PL item parameters
drm(0.0, a = c(1, 2), b = c(0, 1), D = 1)

## Example 3: multiple theta values with a single item (3PL model)
drm(c(-0.1, 0.0, 1.5), a = 1, b = 1, g = 0.2, D = 1)