Estimating Linking Functions for Response Model Parameters

Autor/inn/en	Barrett, Michelle D.; van der Linden, Wim J.
Titel	Estimating Linking Functions for Response Model Parameters
Quelle	In: Journal of Educational and Behavioral Statistics, 44 (2019) 2, S.180-209 (30 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998618808576
Schlagwörter	Item Response Theory; Computation; Error of Measurement; Test Items; Guessing (Tests) + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Messfehler; Test content; Testaufgabe; Erraten
Abstract	Parameter linking in item response theory is generally necessary to adjust for differences between the true values for the same item and ability parameters due to the use of different identifiability restrictions in different calibrations. The research reported in this article explores a precision-weighted (PW) approach to the problem of estimating the linking functions for the common dichotomous logistic response models. Asymptotic standard errors (ASEs) of linking for the new approach are derived and compared to those of the mean/mean and mean/sigma linking methods to which it has a superficial similarity and to the Haebara and Stocking and Lord response function methods. Empirical examples from a few recent linking studies are presented. It is demonstrated that the new approach has smaller ASE than the mean/mean and mean/sigma methods and comparable ASE to the response function methods. However, when some of the item parameters have large estimation error relative to the others, all current methods appear to violate the rather obvious requirement of monotone decrease in ASE with the number of common items in the linking design while the ASE of the PW method demonstrates monotone decrease with the number of common items. The PW method also has the benefits of simple calculation and an ASE which is additive in the contribution of each item, useful for optimal linking design. We conclude that the proposed approach to estimating linking parameters holds promise and warrants further research. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01