GESIS Quicklinks
Intended to bridge the gap between the latest methodological developments and cross-cultural research, this interdisciplinary resource presents the latest strategies for analyzing cross-cultural data. Techniques are demonstrated through the use of applications that employ cross national data ... (Details)
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Part 1. MGCFA and MGSEM Techniques.
Chapter 1: F.J.R. van de Vijver, Capturing Bias in Structural Equation Modeling.
Chapter 2: N. Allum, S. Read, P. Sturgis, Evaluating Change in Social and Political Trust in Europe Using Multiple Group Confirmatory Factor Analysis with Structured Means.
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Chapter 3: J. Lee, T.D. Little, K.J. Preacher, Methodological Issues in Using Structural Equation Models for Testing Differential Item Functioning.
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Chapter 4: H. Steinmetz, Estimation and Comparison of Latent Means Across Cultures.
Chapter 5: A. De Beuckelaer, G. Swinnen, Biased Latent Variable Mean Comparisons Due to Measurement Non-invariance: A Simulation Study.
Chapter 6: E. Davidov, G. Datler, P. Schmidt, S.H. Schwartz, Testing the Invariance of Values in the Benelux Countries with the European Social Survey: Accounting for Ordinality.
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Chapter 7: B. Meuleman, J. Billiet, Religious Involvement: Its Relation to Values and Social Attitudes: A Simultaneous Test of Measurement and Structural Models Across European Countries.
Chapter 8: W.M. van der Veld, W.E. Saris, Causes of Generalized Social Trust: An Innovative Cross-National Evaluation.
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Chapter 9: S. Oreg. Measurement Equivalence using Multi-Group Confirmatory Factor Analysis and Confirmatory Smallest Space Analysis: The Case of Dispositional Resistance to Change.
Part 2. Multilevel Analysis.
Chapter 10: B. Meuleman, Perceived Economic Threat and Anti-immigration Attitudes: Effects of Immigrant Group Size and Economic Conditions Revisited.
Chapter 11: H. Dülmer, A Multilevel Regression Analysis on Work Ethic as a Two-Level Latent Dependent Variable.
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Chapter 12: R. Feskens, J. Hox, Multilevel Structural Equation Modeling for Cross-Cultural Research: Exploring Resampling Methods to Overcome Small Sample Size Problems.
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Part 3. Latent Class Analysis (LCA).
Chapter 13: M. Kankaraš, G. Moors, J.K. Vermunt, Testing for Measurement Invariance with Latent Class Analysis.
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Chapter 14: P. Siegers, A multiple Group Latent Class Analysis of Religious Orientations in Europe.
Part 4. Item Response Theory (IRT).
Chapter 15: R. Janssen, Using a Differential Item Functioning Approach to Investigate Measurement Invariance.
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Chapter 16: M. Quandt, Using the Mixed Rasch Model in the Comparative Analysis of Attitudes.
Chapter 17: J.P. Fox, A.J. Verhagen, Random Item Effects Modeling for Cross-National Survey Data.


