Modeling individual response time effects between and within experimental speed conditions. A GLMM approach for speeded tests.

Autor/inn/en	Goldhammer, Frank; Steinwascher, Merle A.; Kroehne, Ulf; Naumann, Johannes
Titel	Modeling individual response time effects between and within experimental speed conditions. A GLMM approach for speeded tests.
Quelle	In: British Journal of Mathematical and Statistical Psychology, 70 (2017) 2, S. 238-256 PDF als Volltext Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	2044-8317
DOI	10.1111/bmsp.12099
Schlagwörter	Testkonstruktion; Vergleich; Entscheidung; Test; Fehler; Messverfahren; Dauer; Antwort; Einflussfaktor; Modell
Abstract	Completing test items under multiple speed conditions avoids the performance measure being confounded with individual differences in the speed-accuracy compromise, and offers insights into the response process, that is, how response time relates to the probability of a correct response. This relation is traditionally represented by two conceptually different functions: the speed-accuracy trade-off function (SATF) across conditions relating the condition average response time to the condition average of accuracy, and the conditional accuracy function (CAF) within a condition describing accuracy conditional on response time. Using a generalized linear mixed modelling approach, we propose an item response modelling framework that is suitable for item response and response time data from experimental speed conditions. The proposed SATF and CAF model accommodates response time effects between conditions (i.e., person and item SATF slope) and within conditions (i.e., residual CAF slopes), captures person and item differences in these effects, and is suitable for measures with a strong speed component. Moreover, for a single condition a CAF model is proposed distinguishing person, item and residual CAF. The properties of the models are illustrated with an empirical example. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2023/1