Improved Reliability Estimates for Small Samples Using Empirical Bayes Techniques. Research Report. ETS RR-09-46

Autor/inn/en	Oh, Hyeonjoo J.; Guo, Hongwen; Walker, Michael E.
Titel	Improved Reliability Estimates for Small Samples Using Empirical Bayes Techniques. Research Report. ETS RR-09-46
Quelle	In: ETS Research Report Series, (2009), (45 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2330-8516
Schlagwörter	Standardized Tests; Test Reliability; Sample Size; Bayesian Statistics; Accuracy; Error of Measurement; Statistical Distributions; Aptitude Tests; High Schools; College Entrance Examinations; High School Students; Scores; Equations (Mathematics); National Merit Scholarship Qualifying Test; Preliminary Scholastic Aptitude Test + Suchen Sie Ihr Suchwort? Standadised tests; Standardisierter Test; Testreliabilität; Messfehler; Wahrscheinlichkeitsverteilung; Aptitude test; Eignungsprüfung; Eignungstest; High school; Oberschule; Aufnahmeprüfung; High schools; Student; Students; Schüler; Schülerin; Studentin; Equations; Mathematics; Gleichungslehre; Scholarship; Scholarships; Assessment; Stipendium; Hochschulzulassung
Abstract	Issues of equity and fairness across subgroups of the population (e.g., gender or ethnicity) must be seriously considered in any standardized testing program. For this reason, many testing programs require some means for assessing test characteristics, such as reliability, for subgroups of the population. However, often only small sample sizes are available for the subgroups of interest. Traditionally used reliability estimates (e.g., Cronbach's alpha) can have low precision for small samples. This study investigated whether an empirical Bayes (EB) technique could produce more precise reliability estimates than traditional methods in the presence of small samples. Several Bayesian estimates were compared to estimates obtained by other methods (e.g., the traditionally and currently used Cronbach's alpha coefficient), in terms of both bias and variance. A secondary purpose of this study was to compare the various EB approaches across different sample sizes. This paper also discusses EB estimates of standard error of measurement (SEM), their accuracy and precision, and how they compare with SEM estimates derived from the alpha. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01