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Type I error rates of the DIF MIMIC ...

Gelin, Michaela Nicole.

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Type I error rates of the DIF MIMIC approach using Joreskog's covariance matrix with ML and WLS estimation.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Type I error rates of the DIF MIMIC approach using Joreskog's covariance matrix with ML and WLS estimation./
作者:	Gelin, Michaela Nicole.
面頁冊數:	105 p.
附註:	Adviser: Bruno D. Zumbo.
Contained By:	Dissertation Abstracts International66-02B.
標題:	Psychology, Psychometrics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NQ99477
ISBN:	9780612994775

Type I error rates of the DIF MIMIC approach using Joreskog's covariance matrix with ML and WLS estimation.
Gelin, Michaela Nicole.

Type I error rates of the DIF MIMIC approach using Joreskog's covariance matrix with ML and WLS estimation. - 105 p.

Adviser: Bruno D. Zumbo.

Thesis (Ph.D.)--The University of British Columbia (Canada), 2005.

This dissertation presents new research that examines the Type I error rate of a structural equation modeling (SEM) approach for investigating differential item functioning (DIF) in short scales. Specifically Muthen's SEM model for DIF is examined using a new estimation method (Joreskog, 2002). In general, this method conditions on the latent variable while simultaneously testing the effect of the grouping variable over-and-above the underlying latent variable of interest. Thus, it is a multiple-indicators, multiple-causes (MIMIC) model for DIF. The Type I error rates of this DIF MIMIC approach are explored using data that are reflective of short scales with ordinal item response formats typically found in the social and behavioral sciences. The variables included in this Monte Carlo simulation are 7 sample size combinations (3 equal and 4 unequal group combinations), 2 item response distributions (symmetric and positively skewed). 2 scale lengths (10 and 20 items per scale), and 2 estimation methods (maximum likelihood and weighted least-squares). The results indicate that the Type I error rates for the DIF MIMIC model are inflated for both estimation methods under all of the design conditions. These results are discussed in the context of validity including the implications of inflated Type I error rates for items identified as displaying DIF.

ISBN: 9780612994775Subjects--Topical Terms:

1017742
Psychology, Psychometrics.

Type I error rates of the DIF MIMIC approach using Joreskog's covariance matrix with ML and WLS estimation.
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520 $a This dissertation presents new research that examines the Type I error rate of a structural equation modeling (SEM) approach for investigating differential item functioning (DIF) in short scales. Specifically Muthen's SEM model for DIF is examined using a new estimation method (Joreskog, 2002). In general, this method conditions on the latent variable while simultaneously testing the effect of the grouping variable over-and-above the underlying latent variable of interest. Thus, it is a multiple-indicators, multiple-causes (MIMIC) model for DIF. The Type I error rates of this DIF MIMIC approach are explored using data that are reflective of short scales with ordinal item response formats typically found in the social and behavioral sciences. The variables included in this Monte Carlo simulation are 7 sample size combinations (3 equal and 4 unequal group combinations), 2 item response distributions (symmetric and positively skewed). 2 scale lengths (10 and 20 items per scale), and 2 estimation methods (maximum likelihood and weighted least-squares). The results indicate that the Type I error rates for the DIF MIMIC model are inflated for both estimation methods under all of the design conditions. These results are discussed in the context of validity including the implications of inflated Type I error rates for items identified as displaying DIF.
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