calculateIIF {eatATA} | R Documentation |
Calculate Item Information Function
Description
Calculate item information function given item parameters of the 1PL, 2PL or 3PL IRT model.
Usage
calculateIIF(A = rep(1, length(B)), B, C = rep(0, length(B)), theta, D = 1.7)
Arguments
A |
Vector of discrimination parameters. |
B |
Vector of difficulty parameters. |
C |
Vector of pseudo-guessing parameters. |
theta |
Vector of time intensity parameters. |
D |
the constant that should be used. Defaults to 1.7. |
Value
a matrix, with columns for different theta
and rows for different items
References
van der Linden, W. J. (2005). Linear models for optimal test design. New York, NY: Springer.
Examples
# TIF for a single item (2PL model)
calculateIIF(A = 0.8, B = 1.1, theta = 0)
# TIF for multiple items (1PL model)
calculateIIF(B = c(1.1, 0.8, 0.5), theta = 0)
# TIF for multiple theta-values (3PL model)
calculateIIF(B = -0.5, C = 0.25, theta = c(-1, 0, 1))
# TIF for multiple items and multiple ability levels (2PL model)
calculateIIF(A = c(0.7, 1.1, 0.8), B = c(1.1, 0.8, 0.5),
theta = c(-1, 0, 1))
[Package eatATA version 1.1.2 Index]