Measurement Invariance in Comparing Attitudes Toward Immigrants Among Youth Across Europe in 1999 and 2009: The Alignment Method Applied to IEA CIVED and ICCS
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作者:
Munck, Ingrid
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Univ Gothenburg, Dept Educ & Special Educ, Comparat Res Methodol & Stat, Gothenburg, SwedenUniv Gothenburg, Dept Educ & Special Educ, Comparat Res Methodol & Stat, Gothenburg, Sweden
Munck, Ingrid
[1
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Barber, Carolyn
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Univ Missouri, Sch Educ, Educ Psychol, Kansas City, MO 64110 USAUniv Gothenburg, Dept Educ & Special Educ, Comparat Res Methodol & Stat, Gothenburg, Sweden
Barber, Carolyn
[2
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Torney-Purta, Judith
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Univ Maryland, Human Dev, College Pk, MD 20742 USAUniv Gothenburg, Dept Educ & Special Educ, Comparat Res Methodol & Stat, Gothenburg, Sweden
Torney-Purta, Judith
[3
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机构:
[1] Univ Gothenburg, Dept Educ & Special Educ, Comparat Res Methodol & Stat, Gothenburg, Sweden
[2] Univ Missouri, Sch Educ, Educ Psychol, Kansas City, MO 64110 USA
[3] Univ Maryland, Human Dev, College Pk, MD 20742 USA
This study applies the alignment method, a technique for assessing measurement equivalence across many groups, to the analysis of adolescents' support for immigrants' rights in a pooled data set from the 1999 International Association for the Evaluation of Educational Achievement (IEA) Civic Education Study and the 2009 IEA International Civics and Citizenship Education Study. We examined measurement invariance across 92 groups (country by cohort by gender), finding that a five-item scale was statistically well-grounded for unbiased group comparisons despite the presence of significant noninvariance in some groups. Using the resulting group mean scores, we compared European youth's attitudes finding that female students had more positive attitudes than did male students across countries and cohorts. An analysis of countries participating in both studies revealed that students in most countries demonstrated more positive attitudes in 2009 than in 1999. The alignment methodology makes it feasible to comprehensively assess measurement invariance in large data sets and to compute aligned factor scores for the full sample that can update existing databases for more efficient further secondary analysis and with metainformation concerning measurement invariance.