The Effects of Small Sample Size on Identifying Polytomous DIF Using the Liu-Agresti Estimator of the Cumulative Common Odds Ratio.
This study is an evaluation of the behavior of the Liu-Agresti estimator of the cumulative common odds ratio when identifying differential item functioning (DIF) with polytomously scored test items using small samples. The Liu-Agresti estimator has been proposed by Penfield and Algina as a promising...
| Published in: | Educational & Psychological Measurement Vol. 70; no. 6; pp. 914 - 926 |
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| Main Authors: | , |
| Format: | Article |
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Sage Publications Inc.
December 2010
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=508198392&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 508198392 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00131644 EPM jtl: Educational & Psychological Measurement issn: 00131644 maglogo: N pubinfo: dt: December 2010 vid: 70 iid: 6 pid: 344 pub: Sage Publications Inc. artinfo: ui: 508198392 10.1177/0013164410379325 ppf: 914 ppct: 12 formats: tig: atl: The Effects of Small Sample Size on Identifying Polytomous DIF Using the Liu-Agresti Estimator of the Cumulative Common Odds Ratio. aug: au: Carvajal, Jorge Skorupski, William P. su: Psychometrics Estimation theory Statistical sampling sug: subj: Psychometrics Estimation theory Statistical sampling keyword: Differential item functioning ab: This study is an evaluation of the behavior of the Liu-Agresti estimator of the cumulative common odds ratio when identifying differential item functioning (DIF) with polytomously scored test items using small samples. The Liu-Agresti estimator has been proposed by Penfield and Algina as a promising approach for the study of polytomous DIF but no simulation study focusing on small samples has analyzed this estimator regarding effect size, Type I error, and power rates. The article begins with a description of this estimator in the context of polytomous DIF. Then it presents the methods and results for a simulation study in which three factors are manipulated: between-group difference in ability distribution, form of DIF introduced into the polytomous item, and sample size. The results of this study indicate that for samples smaller than 200, very little power was observed for statistical significance testing; however, Type I error rates were close to nominal levels, and the recovery of the log odds ratio as an effect size was relatively unaffected by sample size for high discriminating items. Implications for practice are discussed. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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