A Comparison of Chained Linear and Poststratification Linear Equating under Different Testing Conditions

Autor/in	Puhan, Gautam
Titel	A Comparison of Chained Linear and Poststratification Linear Equating under Different Testing Conditions
Quelle	In: Journal of Educational Measurement, 47 (2010) 1, S.54-75 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/j.1745-3984.2009.00099.x
Schlagwörter	Testing; Equated Scores; Comparative Analysis; Causal Models; Criterion Referenced Tests + Suchen Sie Ihr Suchwort? Testdurchführung; Testen; Kausalanalyse
Abstract	In this study I compared results of chained linear, Tucker, and Levine-observed score equatings under conditions where the new and old forms samples were similar in ability and also when they were different in ability. The length of the anchor test was also varied to examine its effect on the three different equating methods. The three equating methods were compared to a criterion equating to obtain estimates of random equating error, bias, and root mean squared error (RMSE). Results showed that, for most studied conditions, chained linear equating produced fairly good equating results in terms of low bias and RMSE. Levine equating also produced low bias and RMSE in some conditions. Although the Tucker method always produced the lowest random equating error, it produced a larger bias and RMSE than either of the other equating methods. As noted in the literature, these results also suggest that either chained linear or Levine equating be used when new and old form samples differ on ability and/or when the anchor-to-total correlation is not very high. Finally, by testing the missing data assumptions of the three equating methods, this study also shows empirically why an equating method is more or less accurate under certain conditions. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10