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cacIRT  

Classification Accuracy and Consistency under Item Response Theory
View on CRAN: Click here


Download and install cacIRT package within the R console
Install from CRAN:
install.packages("cacIRT")

Install from Github:
library("remotes")
install_github("cran/cacIRT")

Install by package version:
library("remotes")
install_version("cacIRT", "1.4")



Attach the package and use:
library("cacIRT")
Maintained by
Quinn N. Lathrop
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-09-05
Latest Update: 2015-08-28
Description:
Computes classification accuracy and consistency indices under Item Response Theory. Implements the total score IRT-based methods in Lee, Hanson & Brennen (2002) and Lee (2010), the IRT-based methods in Rudner (2001, 2005), and the total score nonparametric methods in Lathrop & Cheng (2014). For dichotomous and polytomous tests.
How to cite:
Quinn N. Lathrop (2011). cacIRT: Classification Accuracy and Consistency under Item Response Theory. R package version 1.4, https://cran.r-project.org/web/packages/cacIRT. Accessed 26 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:23), 1.0 (2011-09-05 22:18), 1.1 (2012-01-27 21:03), 1.2 (2013-11-19 16:55), 1.3 (2014-01-28 16:28)
Other packages that cited cacIRT R package
View cacIRT citation profile
Other R packages that cacIRT depends, imports, suggests or enhances
Complete documentation for cacIRT
Functions, R codes and Examples using the cacIRT R package
Some associated functions: IRT . Lee.ploy . cacIRT-package . cacNP . class.Lee . class.Rud . recursive.raw . 
Some associated R codes: Lee.D.R . Lee.P.R . Lee.pnr.R . Lee.poly.D.R . Lee.poly.P.R . MLE.R . Rud.D.R . Rud.P.R . SEM.R . class.Lee.R . class.Rud.R . gen.rec.raw.R . iif.R . irf.R . normal.qu.R . pnr.R . recursive.raw.R . sim.R . tif.R .  Full cacIRT package functions and examples
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