Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Classification Accuracy and Consistency under Item Response Theory Models Using the Package classify | Wheadon | Journal of Statistical Software
Authors: Chris Wheadon
Title: Classification Accuracy and Consistency under Item Response Theory Models Using the Package classify
Abstract: The R package classify presents a number of useful functions which can be used to estimate the classification accuracy and consistency of assessments. Classification accuracy refers to the probability that an examinees achieved grade classification on an assessment reflects their true grade. Classification consistency refers to the probability that an examinee will be classified into the same grade classification under repeated administrations of an assessment. Understanding the classification accuracy and consistency of assessments is important where key decisions are being taken on the basis of grades or classifications. The study of classification accuracy can help to improve the design of assessments and aid public understanding and confidence in those assessments.

Page views:: 3545. Submitted: 2012-08-23. Published: 2014-01-27.
Paper: Classification Accuracy and Consistency under Item Response Theory Models Using the Package classify     Download PDF (Downloads: 3762)
Supplements:
classify_1.2.tar.gz: R source package Download (Downloads: 234; 25KB)
v56i10.R: R example code from the paper Download (Downloads: 275; 2KB)

DOI: 10.18637/jss.v056.i10

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.