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Statistical tests in the DFIT framew...

University of Missouri - Columbia.

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Statistical tests in the DFIT framework: A Monte Carlo evaluation of conventional methods and a bootstrap alternative.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Statistical tests in the DFIT framework: A Monte Carlo evaluation of conventional methods and a bootstrap alternative./
作者:	Petroski, Gregory F.
面頁冊數:	111 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-09, Section: A, page: 3212.
Contained By:	Dissertation Abstracts International66-09A.
標題:	Education, Educational Psychology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3189946
ISBN:	9780542337215

Statistical tests in the DFIT framework: A Monte Carlo evaluation of conventional methods and a bootstrap alternative.
Petroski, Gregory F.

Statistical tests in the DFIT framework: A Monte Carlo evaluation of conventional methods and a bootstrap alternative. - 111 p.

Source: Dissertation Abstracts International, Volume: 66-09, Section: A, page: 3212.

Thesis (Ph.D.)--University of Missouri - Columbia, 2005.

Item and test bias are forms of test invalidity where unfair advantage is given to some groups of examinees. The judgment of bias requires statistical evidence of differential functioning. Differential item and test functioning (DIF and DTF) occur when individuals with the same ability but from different subgroups of the examinee population have differing probabilities of success on a test item or test. Raju, van der Linden, and Fleer (1992) proposed methods for detecting differential functioning of items and tests (DFIT) in the context of parametric item response theory. The DFIT framework includes tests of significance for DIF and DTF. The purpose of this research was to use simulation methods to study Type I error rates and power characteristics of the conventional DFIT tests for DIF and DTF and several bootstrap alternatives.

ISBN: 9780542337215Subjects--Topical Terms:

1017560
Education, Educational Psychology.

Statistical tests in the DFIT framework: A Monte Carlo evaluation of conventional methods and a bootstrap alternative.
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520 $a Simulation results indicate that the conventional tests have extremely high Type I error rates and their use can no longer be recommended. Bootstrap versions of the tests for DIF and DTF exhibited good control of Type I error and reasonable power when DIF items are excluded from the parameter equating step.
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