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cacIRT (version 1.0)

Computes classification accuracy and consistency under Item Response Theory

Description

Computes classification accuracy and consistency under Item Response Theory by the approach proposed by Lee, Hanson & Brennen (2002) and Lee (2010) or the approach proposed by Rudner (2001, 2005). [Currently, only works for 3PL IRT models (or 2PL or 1PL) (future updates should include polytomous models), and only independent cut scores (imputing multiple cut scores will apply them independently but not simultaneously).]

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Version

Install

install.packages('cacIRT')

Monthly Downloads

428

Version

1.0

License

GPL (>= 2)

Maintainer

Quinn Lathrop

Last Published

September 5th, 2011

Functions in cacIRT (1.0)

MLE

Maximum likelihood estimates of ability
Lee.rec.P

Lee's approach with the P method
Lee.rec.D

Lee's accuracy with D method
cacIRT-package

Classification accuracy and consistency under Item Response Theory
recursive.raw

Recursive computation of conditional total score
Rud.P

Rudner's approach with the P methods
normal.qu

Normal quadrature points and weights
sim

Simulate response data matrix from 3PL model
irf

Item response function
class.Lee

Computes classification accuracy and consistency with Lee's approach.
SEM

Standard error of measurement of MLE estimates of ability
Rud.D

Rudner's approach with D method
class.Rud

Computes classification accuracy and consistency with Rudner's approach.
tif

Test information function
TOtable.F

Classification table for computing True accuracy or consistency
iif

Item information function