Asymptotic expansions for the ability estimator in item response theory
Haruhiko Ogasawara ()
Computational Statistics, 2012, vol. 27, issue 4, 683 pages
Abstract:
Asymptotic approximations to the distributions of the ability estimator and its transformations in item response theory are derived beyond the usual normal one when associated item parameters are given as in tailored testing. For the approximations, the asymptotic cumulants of the estimators up to the fourth order with the higher-order asymptotic variances are obtained under possible model misspecification. For testing and interval estimation of abilities, the asymptotic cumulants of the pivots studentized in four ways are derived. Numerical examples with simulations including those for confidence intervals for abilities are given using the three-parameter logistic model. Copyright Springer-Verlag 2012
Keywords: Ability; Asymptotic expansion; Cumulants; Studentization; Sandwich estimator; Model misspecification; Pivots (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://hdl.handle.net/10.1007/s00180-011-0282-0 (text/html)
Access to full text is restricted to subscribers.
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:spr:compst:v:27:y:2012:i:4:p:661-683
Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2
DOI: 10.1007/s00180-011-0282-0
Access Statistics for this article
Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik
More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().