A General Linear Method for Equating with Small Samples

Autor/in	Albano, Anthony D.
Titel	A General Linear Method for Equating with Small Samples
Quelle	In: Journal of Educational Measurement, 52 (2015) 1, S.55-69 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/jedm.12062
Schlagwörter	Equated Scores; Sample Size; Sampling; Statistical Inference; Comparative Analysis; Accuracy; Computation; Statistical Analysis + Suchen Sie Ihr Suchwort? Inferential statistics; Schließende Statistik; Statistische Analyse
Abstract	Research on equating with small samples has shown that methods with stronger assumptions and fewer statistical estimates can lead to decreased error in the estimated equating function. This article introduces a new approach to linear observed-score equating, one which provides flexible control over how form difficulty is assumed versus estimated to change across the score scale. A general linear method is presented as an extension of traditional linear methods. The general method is then compared to other linear and nonlinear methods in terms of accuracy in estimating a criterion equating function. Results from two parametric bootstrapping studies based on real data demonstrate the usefulness of the general linear method. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01