normaliseIRT: normaliseIRT

In cdriveraus/bigIRT: Fits item response theory models to big data

normaliseIRT

Description

Normalise item response theory (IRT) parameters.

Usage

normaliseIRT(
  B,
  Ability,
  A,
  normbase = "Ability",
  normaliseScale = 1,
  normaliseMean = ifelse(normbase == "A", 1, 0),
  robust = TRUE
)

Arguments

B	Vector of item difficulty parameters.
Ability	Vector of persons' ability parameters.
A	Vector of item discrimination parameters.
normbase	The base from which the normalisation should be calculated. Can be 'Ability' or 'B'.
normaliseScale	The scale to normalise to.
normaliseMean	The mean to normalise to. The default is 0 when normbase is 'Ability' or 'B', and 1 when normbase is 'A'.
robust	if TRUE, outliers (greater than 1.5x the interquartile range from the interquartile region of 25-75%) are dropped before computing the mean and sd for normalisation.

Value

A list containing the normalised A, B, and Ability parameters.

Examples

B <- rnorm(100,2,1)
Ability <- rnorm(500,3,.5)
A <- rnorm(100,1.4,.05)
normaliseIRT(B, Ability, A, normbase='B')

cdriveraus/bigIRT documentation built on Sept. 14, 2024, 5:42 a.m.