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Comparing Performances (Type I error and Power) of IRT Likelihood Ratio SIBTEST and Mantel-Haenszel Methods in the Determination of Differential Item Functioning
This simulation study compared the performances (Type I error and power) of Mantel-Haenszel (MH), SIBTEST, and item response theory-likelihood ratio (IRT-LR) methods under certain conditions. Manipulated factors were sample size, ability differences between groups, test length, the percentage of dif...
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Published in: | Educational sciences : theory & practice 2014-01, Vol.14 (6), p.2186 |
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description | This simulation study compared the performances (Type I error and power) of Mantel-Haenszel (MH), SIBTEST, and item response theory-likelihood ratio (IRT-LR) methods under certain conditions. Manipulated factors were sample size, ability differences between groups, test length, the percentage of differential item functioning (DIF), and underlying model used to generate data. Results suggest that SIBTEST had the highest Type I error in the detection of uniform DIF, but MH had the highest power under all conditions. In addition, the percentage of DIF and the underlying model appear to have influenced the Type I error rate of IRT-LR. Ability differences between groups, test length, the percentage of DIF, model, and the interactions between ability differences*percentage of DIF, ability differences*test length, test length*percentage of DIF, test length*model affected the SIBTEST methods' Type I error rate. In the MH procedure, effective factors for Type I error rate were: sample size, test length, the percentage of DIF, ability differences*percentage of DIF, ability differences*model, and ability differences*percentage of DIF*model. No factors were effective on the power of SIBTEST and MH, but the underlying model had a significant effect on the IRT-LR power rate. |
doi_str_mv | 10.12738/estp.2014.6.2165 |
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Manipulated factors were sample size, ability differences between groups, test length, the percentage of differential item functioning (DIF), and underlying model used to generate data. Results suggest that SIBTEST had the highest Type I error in the detection of uniform DIF, but MH had the highest power under all conditions. In addition, the percentage of DIF and the underlying model appear to have influenced the Type I error rate of IRT-LR. Ability differences between groups, test length, the percentage of DIF, model, and the interactions between ability differences*percentage of DIF, ability differences*test length, test length*percentage of DIF, test length*model affected the SIBTEST methods' Type I error rate. In the MH procedure, effective factors for Type I error rate were: sample size, test length, the percentage of DIF, ability differences*percentage of DIF, ability differences*model, and ability differences*percentage of DIF*model. 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Manipulated factors were sample size, ability differences between groups, test length, the percentage of differential item functioning (DIF), and underlying model used to generate data. Results suggest that SIBTEST had the highest Type I error in the detection of uniform DIF, but MH had the highest power under all conditions. In addition, the percentage of DIF and the underlying model appear to have influenced the Type I error rate of IRT-LR. Ability differences between groups, test length, the percentage of DIF, model, and the interactions between ability differences*percentage of DIF, ability differences*test length, test length*percentage of DIF, test length*model affected the SIBTEST methods' Type I error rate. In the MH procedure, effective factors for Type I error rate were: sample size, test length, the percentage of DIF, ability differences*percentage of DIF, ability differences*model, and ability differences*percentage of DIF*model. 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Gök, Bilge ; Arsan, Nihan ; Kelecioglu, Hülya</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c295t-a2ab19957735772f5650b8b3f01fbe942424af0b6611f06c6ba29f27de1baef03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Ability</topic><topic>Comparative Analysis</topic><topic>Differences</topic><topic>Error of Measurement</topic><topic>Foreign Countries</topic><topic>Item Response Theory</topic><topic>Mantel Haenszel Procedure</topic><topic>Sample Size</topic><topic>Simulation</topic><topic>Statistical Analysis</topic><topic>Test Bias</topic><topic>Test Items</topic><topic>Test Length</topic><topic>Turkey</topic><toplevel>online_resources</toplevel><creatorcontrib>Kabasakal, Kübra Atalay</creatorcontrib><creatorcontrib>Gök, Bilge</creatorcontrib><creatorcontrib>Arsan, Nihan</creatorcontrib><creatorcontrib>Kelecioglu, Hülya</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Education Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Education Collection</collection><collection>ProQuest Central Korea</collection><collection>Turkey Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Education Database (ProQuest)</collection><collection>ProQuest Psychology</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>ERIC</collection><collection>ERIC - Full Text Only (Discovery)</collection><jtitle>Educational sciences : theory & practice</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kabasakal, Kübra Atalay</au><au>Gök, Bilge</au><au>Arsan, Nihan</au><au>Kelecioglu, Hülya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1050496</ericid><atitle>Comparing Performances (Type I error and Power) of IRT Likelihood Ratio SIBTEST and Mantel-Haenszel Methods in the Determination of Differential Item Functioning</atitle><jtitle>Educational sciences : theory & practice</jtitle><date>2014-01-01</date><risdate>2014</risdate><volume>14</volume><issue>6</issue><spage>2186</spage><pages>2186-</pages><issn>2148-7561</issn><issn>1303-0485</issn><eissn>2148-7561</eissn><abstract>This simulation study compared the performances (Type I error and power) of Mantel-Haenszel (MH), SIBTEST, and item response theory-likelihood ratio (IRT-LR) methods under certain conditions. Manipulated factors were sample size, ability differences between groups, test length, the percentage of differential item functioning (DIF), and underlying model used to generate data. Results suggest that SIBTEST had the highest Type I error in the detection of uniform DIF, but MH had the highest power under all conditions. In addition, the percentage of DIF and the underlying model appear to have influenced the Type I error rate of IRT-LR. Ability differences between groups, test length, the percentage of DIF, model, and the interactions between ability differences*percentage of DIF, ability differences*test length, test length*percentage of DIF, test length*model affected the SIBTEST methods' Type I error rate. In the MH procedure, effective factors for Type I error rate were: sample size, test length, the percentage of DIF, ability differences*percentage of DIF, ability differences*model, and ability differences*percentage of DIF*model. No factors were effective on the power of SIBTEST and MH, but the underlying model had a significant effect on the IRT-LR power rate.</abstract><cop>Istanbul</cop><pub>EDAM (Educational Consultancy Ltd.)</pub><doi>10.12738/estp.2014.6.2165</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Ability Comparative Analysis Differences Error of Measurement Foreign Countries Item Response Theory Mantel Haenszel Procedure Sample Size Simulation Statistical Analysis Test Bias Test Items Test Length Turkey |
title | Comparing Performances (Type I error and Power) of IRT Likelihood Ratio SIBTEST and Mantel-Haenszel Methods in the Determination of Differential Item Functioning |
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