MIMIC approach to assessing differential item functioning with control of extreme response style
Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item func...
Ausführliche Beschreibung
Autor*in: |
Jin, Kuan-Yu [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Schlagwörter: |
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Anmerkung: |
© The author's 2019 |
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Übergeordnetes Werk: |
Enthalten in: Behavior research methods, instruments & computers - Austin, Tex. : Psychonomic Society Publ., 1984, 52(2019), 1 vom: 31. Jan., Seite 23-35 |
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Übergeordnetes Werk: |
volume:52 ; year:2019 ; number:1 ; day:31 ; month:01 ; pages:23-35 |
Links: |
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DOI / URN: |
10.3758/s13428-019-01198-1 |
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Katalog-ID: |
SPR031711197 |
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10.3758/s13428-019-01198-1 doi (DE-627)SPR031711197 (SPR)s13428-019-01198-1-e DE-627 ger DE-627 rakwb eng Jin, Kuan-Yu verfasserin aut MIMIC approach to assessing differential item functioning with control of extreme response style 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The author's 2019 Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. Extreme response style (dpeaa)DE-He213 Multiple indicators multiple causes (dpeaa)DE-He213 Differential item functioning (dpeaa)DE-He213 Measurement invariance (dpeaa)DE-He213 Chen, Hui-Fang aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 52(2019), 1 vom: 31. Jan., Seite 23-35 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:52 year:2019 number:1 day:31 month:01 pages:23-35 https://dx.doi.org/10.3758/s13428-019-01198-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 52 2019 1 31 01 23-35 |
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10.3758/s13428-019-01198-1 doi (DE-627)SPR031711197 (SPR)s13428-019-01198-1-e DE-627 ger DE-627 rakwb eng Jin, Kuan-Yu verfasserin aut MIMIC approach to assessing differential item functioning with control of extreme response style 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The author's 2019 Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. Extreme response style (dpeaa)DE-He213 Multiple indicators multiple causes (dpeaa)DE-He213 Differential item functioning (dpeaa)DE-He213 Measurement invariance (dpeaa)DE-He213 Chen, Hui-Fang aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 52(2019), 1 vom: 31. Jan., Seite 23-35 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:52 year:2019 number:1 day:31 month:01 pages:23-35 https://dx.doi.org/10.3758/s13428-019-01198-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 52 2019 1 31 01 23-35 |
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10.3758/s13428-019-01198-1 doi (DE-627)SPR031711197 (SPR)s13428-019-01198-1-e DE-627 ger DE-627 rakwb eng Jin, Kuan-Yu verfasserin aut MIMIC approach to assessing differential item functioning with control of extreme response style 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The author's 2019 Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. Extreme response style (dpeaa)DE-He213 Multiple indicators multiple causes (dpeaa)DE-He213 Differential item functioning (dpeaa)DE-He213 Measurement invariance (dpeaa)DE-He213 Chen, Hui-Fang aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 52(2019), 1 vom: 31. Jan., Seite 23-35 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:52 year:2019 number:1 day:31 month:01 pages:23-35 https://dx.doi.org/10.3758/s13428-019-01198-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 52 2019 1 31 01 23-35 |
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10.3758/s13428-019-01198-1 doi (DE-627)SPR031711197 (SPR)s13428-019-01198-1-e DE-627 ger DE-627 rakwb eng Jin, Kuan-Yu verfasserin aut MIMIC approach to assessing differential item functioning with control of extreme response style 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The author's 2019 Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. Extreme response style (dpeaa)DE-He213 Multiple indicators multiple causes (dpeaa)DE-He213 Differential item functioning (dpeaa)DE-He213 Measurement invariance (dpeaa)DE-He213 Chen, Hui-Fang aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 52(2019), 1 vom: 31. Jan., Seite 23-35 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:52 year:2019 number:1 day:31 month:01 pages:23-35 https://dx.doi.org/10.3758/s13428-019-01198-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 52 2019 1 31 01 23-35 |
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10.3758/s13428-019-01198-1 doi (DE-627)SPR031711197 (SPR)s13428-019-01198-1-e DE-627 ger DE-627 rakwb eng Jin, Kuan-Yu verfasserin aut MIMIC approach to assessing differential item functioning with control of extreme response style 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The author's 2019 Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. Extreme response style (dpeaa)DE-He213 Multiple indicators multiple causes (dpeaa)DE-He213 Differential item functioning (dpeaa)DE-He213 Measurement invariance (dpeaa)DE-He213 Chen, Hui-Fang aut Enthalten in Behavior research methods, instruments & computers Austin, Tex. : Psychonomic Society Publ., 1984 52(2019), 1 vom: 31. Jan., Seite 23-35 (DE-627)32998067X (DE-600)2048669-8 1532-5970 nnns volume:52 year:2019 number:1 day:31 month:01 pages:23-35 https://dx.doi.org/10.3758/s13428-019-01198-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 AR 52 2019 1 31 01 23-35 |
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MIMIC approach to assessing differential item functioning with control of extreme response style Extreme response style (dpeaa)DE-He213 Multiple indicators multiple causes (dpeaa)DE-He213 Differential item functioning (dpeaa)DE-He213 Measurement invariance (dpeaa)DE-He213 |
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mimic approach to assessing differential item functioning with control of extreme response style |
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MIMIC approach to assessing differential item functioning with control of extreme response style |
abstract |
Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. © The author's 2019 |
abstractGer |
Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. © The author's 2019 |
abstract_unstemmed |
Abstract Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model. © The author's 2019 |
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