Factorial Structure of the Family Values Scale From a Multilevel-Multicultural Perspective

REFERENCES

• Bentler, P.M. (2005). EQS 6 structural equations program manual. Encino, CA: Multivariate Software Inc.
   Google Scholar
• Bovaird, J.A. (2007). Multilevel structural equation models for contextual factors. In T.D. Little, J.A. Bovaird, & N.A. Card (Eds.), Modeling contextual effects in longitudinal studies (pp. 149–182). Mahwah, NJ: Erlbaum.
   Google Scholar
• Bryk, A.S., & Raudenbush, S.W. (1987). Applications of hierarchical linear models to assessing change. Psychological Bulletin, 101, 147–158. doi:10.1037/0033–2909.101.1.147
   Web of Science ®Google Scholar
• Byrne, B.M. (2005). Factor analytic models: Viewing the structure of an assessment instrument from three perspectives. Journal of Personality Assessment, 85, 17–30. . doi:10.1207/s15327752jpa8501_02
   PubMed Web of Science ®Google Scholar
• Byrne, B.M. (2011). Structural equation modeling with Mplus: Basic concepts, applications, and programming. New York, NY: Taylor & Francis/Routledge.
   Google Scholar
• Byrne, B.M., & van de Vijver, F.J. R. (2010). Testing for measurement and structural equivalence in large-scale cross-cultural studies: Addressing the issue of nonequivalence. International Journal of Testing, 10, 107–132. . doi:10.1080/15305051003637306
   Google Scholar
• Cheung, M.W.-L., & Au, K. (2005). Applications of multilevel structural equation modeling to cross-cultural research. Structural Equation Modeling, 12, 598–619. . doi:10.1207/s15328007sem1204_5
   Web of Science ®Google Scholar
• Cheung, M.W.-L., Leung, K., & Au, K. (2006). Evaluating multilevel models in cross cultural research: An illustration with social axioms. Journal of Cross-Cultural Psychology, 37, 522–541. . doi:10.1177/0022022106290476
   Web of Science ®Google Scholar
• Curran, P.J., West, S.G., & Finch, J.F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1, 16–29. . doi:10.1037/1082–989X.1.1.16
   Web of Science ®Google Scholar
• Davidov, E. (2008). A cross-country and cross-time comparison of human values measurements with the second round of the European Social Survey. Survey Research Methods, 2, 33–46.
   Google Scholar
• Dedrick, R.F., & Greenbaum, P.E. (2010). Multilevel confirmatory factor analysis of a scale measuring interagency collaboration of children's mental health agencies. Journal of Emotional and Behavioral Disorders, 19, 27–40. . doi:10.1177/1063426610365879
   Web of Science ®Google Scholar
• Feskens, R., & Hox, J.J. (2011). Multilevel structural equation modeling for cross-cultural research: Exploring resampling methods to overcome small sample size problems. In E. Davidov, P. Schmidt, & J. Billiet (Eds.), Cross-cultural analysis: Methods and applications (pp. 341–356). New York, NY: Taylor & Francis/Routledge.
   Google Scholar
• Floyd, F.J., & Widaman, K.F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7, 286–299. . doi:10.1037/1040–3590.7.3.286
   Web of Science ®Google Scholar
• Georgas, J. (1989). Changing family values in Greece from collectivist to individualist. Journal of Cross-Cultural Psychology, 20, 80–91. . doi:10.1177/0022022189201005
   Web of Science ®Google Scholar
• Georgas, J. (1999). Family as a context variable in cross-cultural psychology. In J. Adamopoulos & Y. Kashima (Eds.), Social psychology and cultural context (pp. 163–175). Beverly Hills, CA: Sage. . doi:10.4135/9781452220550.n12
   Google Scholar
• Georgas, J., van de Vijver, F.J. R., & Berry, J.W. (2004). The ecocultural framework, ecosocial indices and psychological variables in cross-cultural research. Journal of Cross-Cultural Psychology, 35, 74–96. . doi:10.1177/0022022103260459
   Web of Science ®Google Scholar
• Heck, R.H. (2001). Multilevel modeling with SEM. In G.A. Marcoulides & R.E. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 89–127). Mahwah, NJ: Erlbaum.
   Google Scholar
• Heck, R.H., & Thomas, S.L. (2009). An introduction to multilevel modeling techniques . (2nd ed.). New York, NY: Routledge
   Google Scholar
• Horn, J.L., & McArdle, J.J. (1992). A practical and theoretical guide to measurement equivalence in aging research. Experimental Aging Research, 18, 117–144. . doi:10.1080/03610739208253916
   PubMed Web of Science ®Google Scholar
• Hox, J.J., & Maas, C.J. M. (2001). The accuracy of multilevel structural equation modeling with pseudobalanced groups and small samples. Structural Equation Modeling, 8, 157–174. . doi:10.1207/S15328007SEM0802_1
   Web of Science ®Google Scholar
• Hox, J., van de Schoot, R., & Matthijsse, S. (2012). How few countries will do? Comparative survey analysis from a Bayesian perspective. Survey Research Methods, 6, 87–93.
   Web of Science ®Google Scholar
• Jöreskog, K.G. (1971). Simultaneous factor analysis in several populations. Psychometrika, 36, 409–426. . doi:10.1007/BF02291366
   Web of Science ®Google Scholar
• Julian, M.W. (2001). The consequences of ignoring multilevel data structures in nonhierarchical covariance modeling. Structural Equation Modeling, 8, 325–352. . doi:10.1207/S15328007SEM0803_1
   Web of Science ®Google Scholar
• Kaplan, D., & Elliott, P.R. (1997). A didactic example of multilevel structural equation modeling applicable to the study of organizations. Structural Equation Modeling, 4, 1–24. . doi:10.1080/10705519709540056
   Web of Science ®Google Scholar
• Kreft, I., & de Leeuw, J. (1998). Introducing multilevel modeling. Newbury Park, CA: Sage.
   Google Scholar
• Marsh, H., Dowson, M., Pietsch, J., & Walker, R. (2004). Why multicollinearity matters: A reexamination of relations between self-efficacy, self-concept, and achievement. Journal of Educational Psychology, 96, 518–522. . doi:10.1037/0022–0663.96.3.518
   Web of Science ®Google Scholar
• Mehta, P.D., & Neale, M.C. (2005). People are variables too: Multilevel structural equations modeling. Psychological Methods, 10, 259–284. . doi:10.1037/1082–989X.10.3.259
   PubMed Web of Science ®Google Scholar
• Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58, 525–543. . doi:10.1007/BF02294825
   Web of Science ®Google Scholar
• Meuleman, B., & Billiet, J. (2009). A Monte Carlo sample size study: How many countries are needed for accurate multilevel SEM? Survey Research Methods, 3, 45–58.
   Google Scholar
• Muthén, B.O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22, 376–398. . doi:10.1177/0049124194022003006
   Web of Science ®Google Scholar
• Muthén, B.O., & Satorra, A. (1995). Complex sample data in structural equation modeling. In P. Marsden (Ed.), Sociological methodology 1995 (pp. 267–316). Washington, DC: American Sociological Association.
   Google Scholar
• Muthén, L.K., & Muthén, B.O. (2007–2010). Mplus user's guide . (6th ed.). Los Angeles, CA: Authors.
   Google Scholar
• Mylonas, K., Pavlopoulos, V., & Georgas, J. (2008). Multilevel structure analysis for family-related constructs. In F.J. R. van de Vijver, D.A. van Hemert, & Y.H. Poortinga (Eds.), Multilevel analysis of individuals and cultures (pp. 345–377). New York, NY: Taylor & Francis.
   Google Scholar
• Robinson, W.S. (1950). Ecological correlations and the behaviors of individuals. American Sociological Review, 15, 351–357. . doi:10.2307/2087176
   Web of Science ®Google Scholar
• Ryu, E., & West, S.G. (2009). Level-specific evaluation of model fit in multilevel structural equation modeling. Structural Equation Modeling, 16, 583–601. . doi:10.1080/10705510903203466
   Web of Science ®Google Scholar
• Selig, J.P., Card, N.A., & Little, T.D. (2008). Latent variable structural equation modeling in cross-cultural research: Multigroup and multilevel approaches. In F.J. R. van de Vijver, D.A. van Hemert, & Y.H. Poortinga (Eds.), Multilevel analysis of individuals and cultures (pp. 93–119). New York, NY: Taylor & Francis.
   Google Scholar
• van de Vijver, F.J. R. (2011). Capturing bias in structural equation modeling. In E. Davidov, P. Schmidt, & J. Billiet (Eds.), Cross-cultural analysis: Methods and applications (pp. 3–34). New York, NY: Taylor & Francis/Routledge.
   Google Scholar
• van de Vijver, F.J. R., & Leung, K. (1997). Methods and data analysis for cross-cultural research. Thousand Oaks, CA: Sage.
   Google Scholar
• van de Vijver, F.J. R., & Leung, K. (2000). Methodological issues in psychological research on culture. Journal of Cross-Cultural Psychology, 31, 33–51. . doi:10.1177/0022022100031001004
   Web of Science ®Google Scholar
• van de Vijver, F.J. R., Mylonas, K., Pavlopoulos, V., & Georgas, J. (2006). Results: Cross-cultural analyses of the family. In J. Georgas, J.W. Berry, F.J. R. van de Vijver, C. Kagitcibasi, & Y.H. Poortinga (Eds.), Families across culture: A 30-nation psychological study (pp. 126–185). Cambridge, UK: Cambridge University Press. . doi:10.1017/CBO9780511489822.008
   Google Scholar
• van de Vijver, F.J. R., & Poortinga, Y.H. (2002). Structural equivalence in multilevel research. Journal of Cross-Cultural Psychology, 33, 141–156. . doi:10.1177/0022022102033002002
   Web of Science ®Google Scholar
• van de Vijver, F.J. R., & Watkins, D. (2006). Assessing similarity of meaning at individual and country level: An investigation of a measure of independent and interdependent self. European Journal of Psychological Assessment, 22, 69–77. . doi:10.1027/1015–5759.22.2.69
   Web of Science ®Google Scholar
• Widaman, K.F., & Reise, S.P. (1997). Exploring the measurement invariance of psychological instruments in the substance use domain. In K.J. Bryant, M. Windle, & S.G. West (Eds.), The science of prevention. Methodological advances from alcohol and substance abuse research (pp. 281–324). Washington, DC: American Psychological Association. . doi:10.1037/10222–009
   Google Scholar
• Williams, J.E., & Best, D.L. (1982). Measuring sex stereotypes: A thirty nation study. Beverly Hills, CA: Sage.
   Google Scholar
• Williams, J.E., & Best, D.L. (1990). Measuring sex stereotypes: A multination study. Beverly Hills, CA: Sage.
   Google Scholar