Performing the Kernel Method of Test Equating with the Package kequate
Björn Andersson,
Kenny Bränberg and
Marie Wiberg
Journal of Statistical Software, 2013, vol. 055, issue i06
Abstract:
In standardized testing it is important to equate tests in order to ensure that the test takers, regardless of the test version given, obtain a fair test. Recently, the kernel method of test equating, which is a conjoint framework of test equating, has gained popularity. The kernel method of test equating includes five steps: (1) pre-smoothing, (2) estimation of the score probabilities, (3) continuization, (4) equating, and (5) computing the standard error of equating and the standard error of equating difference. Here, an implementation has been made for six different equating designs: equivalent groups, single group, counter balanced, non-equivalent groups with anchor test using either chain equating or post- stratification equating, and non-equivalent groups using covariates. An R package for the kernel method of test equating called kequate is presented. Included in the package are also diagnostic tools aiding in the search for a proper log-linear model in the pre-smoothing step for use in conjunction with the R function glm.
Date: 2013-10-22
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v055i06/v55i06.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... kequate_1.3.2.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v055i06/v55i06.R
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:055:i06
DOI: 10.18637/jss.v055.i06
Access Statistics for this article
Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis
More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().