On the Statistical and Practical Limitations of Thurstonian IRT Models

Autor/inn/en	Bürkner, Paul-Christian; Schulte, Niklas; Holling, Heinz
Titel	On the Statistical and Practical Limitations of Thurstonian IRT Models
Quelle	In: Educational and Psychological Measurement, 79 (2019) 5, S.827-854 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Bürkner, Paul-Christian)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164419832063
Schlagwörter	Item Response Theory; Measurement Techniques; Questionnaires; Rating Scales; Scores; Response Style (Tests); Bias; Test Items; Statistical Analysis + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Messtechnik; Fragebogen; Rating-Skala; Antwortverhalten; Test content; Testaufgabe; Statistische Analyse
Abstract	Forced-choice questionnaires have been proposed to avoid common response biases typically associated with rating scale questionnaires. To overcome ipsativity issues of trait scores obtained from classical scoring approaches of forced-choice items, advanced methods from item response theory (IRT) such as the Thurstonian IRT model have been proposed. For convenient model specification, we introduce the thurstonianIRT R package, which uses Mplus, lavaan, and Stan for model estimation. Based on practical considerations, we establish that items within one block need to be equally keyed to achieve similar social desirability, which is essential for creating forced-choice questionnaires that have the potential to resist faking intentions. According to extensive simulations, measuring up to five traits using blocks of only equally keyed items does not yield sufficiently accurate trait scores and inter-trait correlation estimates, neither for frequentist nor for Bayesian estimation methods. As a result, persons' trait scores remain partially ipsative and, thus, do not allow for valid comparisons between persons. However, we demonstrate that trait scores based on only equally keyed blocks can be improved substantially by measuring a sizable number of traits. More specifically, in our simulations of 30 traits, scores based on only equally keyed blocks were non-ipsative and highly accurate. We conclude that in high-stakes situations where persons are motivated to give fake answers, Thurstonian IRT models should only be applied to tests measuring a sizable number of traits. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01