Skip to main content
SpringerLink
Log in

How to Obtain Comparable Measures for Cross-National Comparisons

Wie kann man invariante Messungen in international vergleichender Forschung erhalten?

  • Abhandlungen
  • Published:
KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie Aims and scope Submit manuscript

Abstract

Comparisons of means or associations between theoretical constructs of interest in cross-national comparative research assume measurement invariance, that is, that the same constructs are measured in the same way across the various nations under study. While it is intuitive, this assumption needs to be statistically tested. An increasing number of sociological and social psychological studies have been published in the last decade in which the cross-national comparability of various scales such as human values, national identity, attitudes toward democracy, or religiosity, to name but a few, were tested. Many of these studies did not manage to fully achieve measurement invariance. In this study we review, in a nontechnical manner, the methodological literature on measurement invariance testing. We explain what it is, how to test for it, and what to do when measurement invariance across countries is not given in the data. Several approaches have been recently proposed in the literature on how to deal with measurement noninvariance. We illustrate one of these approaches with a large dataset of seven rounds from the European Social Survey (2002–2015) by estimating the most trustworthy means of human values, even when strict measurement invariance is not given in the data. We conclude with a summary and some critical remarks.

Zusammenfassung

Vergleiche von Mittelwerten und von Beziehungen zwischen theoretischen Konstrukten, die im Rahmen international vergleichender Forschung untersucht werden, gehen davon aus, dass diese Konstrukte messinvariant sind, d. h., dass sie in den verschiedenen Ländern identisch gemessen werden. Obwohl diese Annahme plausibel sein kann, muss sie jedoch statistisch getestet werden. Im letzten Jahrzehnt wurde eine zunehmende Zahl von soziologischen, politikwissenschaftlichen und sozialpsychologischen Studien veröffentlicht, in denen die internationale Vergleichbarkeit von verschiedenen Skalen zur Messung von z. B. menschlichen Werten, nationaler Identität, Einstellungen zu Demokratie oder Religiosität überprüft wurde. In vielen dieser Studien konnte Messinvarianz nicht völlig nachgewiesen werden. Die folgende Studie bietet in einer nicht technischen Art und Weise einen Überblick über die methodologische Literatur zur Messinvarianz. Es wird erklärt, was Messinvarianz ist, wie man sie überprüft und was man tun kann, wenn sie in den Daten nicht gegeben ist. In der Literatur wurden in der letzten Zeit verschiedene Ansätze vorgeschlagen, wie man fehlende Messinvarianz behandeln kann. Die Autoren illustrieren eine dieser Herangehensweisen (Alignment) mit einem großen Datensatz, der 7 Befragungsrunden des European Social Survey (2002–2015) beinhaltet, und schätzen den vertrauenswürdigsten Durchschnitt menschlicher Werte, auch wenn strikte Messinvarianz in den Daten nicht vorhanden ist. Abschließend folgen eine Zusammenfassung und einige kritische Anmerkungen.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Researchers examine global fit measures and perform chi-square difference tests to determine whether a more highly restricted model is supported by the data, that is if a higher level of invariance is given. However, based on a Monte Carlo study, Chen (2007) proposed an alternative to the chi-square difference test, which leads too easily to a rejection of measurement invariance. He proposed that metric noninvariance is indicated by a change smaller than 0.01 in the comparative fit index (CFI), supplemented by a change smaller than 0.015 in the root mean square error of approximation (RMSEA), or a change smaller than 0.03 in the standardized root mean square residual (SRMR) compared with the configural invariance model. To guarantee scalar invariance, Chen (2007) proposed to inspect whether the change in CFI is smaller than 0.01, the change in RMSEA is smaller than 0.015, or the change in SRMR is smaller than 0.01, when moving from a metric to a scalar invariance model for sample sizes larger than 300 per group.

  2. Measures of the Schwartz values are also included in other international surveys such as the World Values Survey or the U.S. General Social Survey (for further details, see http://www.worldvaluessurvey.org/wvs.jsp; http://www.norc.org/Research/Projects/Pages/general-social-survey.aspx).

  3. The authors excluded the value ‘hedonism’ from this model. According to the theory, this value is located between openness to change and self-enhancement. Including this value in either of the models resulted in a significant reduction in model fit.

  4. The scale of latent variables is unknown, and hence their variance is also unknown (by definition, these variables are unobserved). Therefore, in order to identify the model, researchers need to apply some restriction for the estimation: either restricting the variance of the latent variable to an arbitrary value (typically it is then restricted to 1 in all groups), or fixing the scale of the latent variable by restricting the factor loading of one of the items (the so-called anchor item) to 1 in all groups. When doing so, it is important to guarantee that such a restriction fits the data at hand. In the former case, the restriction implies an implicit assumption that the latent variance is equal across groups. In the latter case, the restriction implies that the factor loading of the anchor item is indeed equal across groups. In both cases, researchers need to make sure that the assumption holds, for example by inspecting which of these parameters (factor loading of one of the items or the latent variable variance) are indeed most similar across groups, and choose the restriction which best corresponds with the data at hand (see also Brown 2015, p. 271).

  5. Many studies evidenced that intercepts were not equal across groups, and that it was easier to guarantee equal factor loadings than equal intercepts when comparing different countries (see e. g. Davidov et al. 2014). In other words, it was often easier to establish metric invariance than scalar invariance. Different intercepts may also reflect different country-specific survey strategies, which in turn may result in different response patterns across countries.

  6. Tables that display more highly specific information about the (non)invariance pattern for each higher-order value may be obtained from the first author on request. They present the number of noninvariant loadings and intercepts for each item and country. One way to estimate the amount of bias, discussed in Oberski (2014), is to perform a sensitivity analysis.

  7. Methodologists also discuss the topic of isomorphism, which refers to equivalent construct meaning across levels of analysis. In other words, it refers to the presence or absence of measurement invariance across levels, for example across individuals and countries. However, examining isomorphism in cross-national data settings is beyond the scope of the present study (for a further discussion, see e. g. Guenole 2016; Muthén 1994; or Ruelens et al. 2016).

References

  • Aleman, Jose, and Dwayne Woods. 2016. Value orientations from the World Value Survey: How comparable are they cross-nationally? Comparative Political Studies 49:1039–1067. https://doi.org/10.1177/0010414015600458

    Article  Google Scholar 

  • Ariely, Gal, and Eldad Davidov. 2010. Can we rate public support for democracy in a comparable way? Cross-national equivalence of democratic attitudes in the World Value Survey. Social Indicators Research 104:271–286.

    Article  Google Scholar 

  • Asparouhov, Tihomir, and Bengt O. Muthén. 2014. Multi-group factor analysis Alignment. Structural Equation Modeling 21:1–14. https://doi.org/10.1080/10705511.2014.919210

    Article  Google Scholar 

  • Beierlein, Constanze, Eldad Davidov, Peter Schmidt, Shalom H. Schwartz and Beatrice Rammstedt. 2012. Testing the discriminant validity of Schwartz’ Portrait Value Questionnaire items—A replication and extension of Knoppen and Saris (2009). Survey Research Methods 6:25–36.

    Google Scholar 

  • Bilsky, Wolfgang, Michael Janik and Shalom H. Schwartz. 2011. The structural organization of human values—Evidence from three rounds of the European Social Survey (ESS). Journal of Cross-Cultural Psychology 42:759–776. https://doi.org/10.1177/0022022110362757

    Article  Google Scholar 

  • Brown, Timothy A. 2015. Confirmatory factor analysis for applied research. New York: Guilford Press.

    Google Scholar 

  • Byrne, Barbara M., Richard J. Shavelson and Bengt O. Muthén. 1989. Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin 105:456–466. https://doi.org/10.1207/s15328007sem1102_8

    Article  Google Scholar 

  • Chen, Fang F. 2007. Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling 14:464–504. https://doi.org/10.1080/10705510701301834

    Article  Google Scholar 

  • Chen, Fang F. 2008. What happens if we compare chopsticks with forks? The impact of making inappropriate comparison in cross-cultural research. Journal of Personality and Social Psychology 95:1005–1018. https://doi.org/10.1037/a0013193

    Article  Google Scholar 

  • Cieciuch, Jan, and Eldad Davidov. 2012. A comparison of the invariance properties of the PVQ-40 and the PVQ-21 to measure human values across German and Polish samples. Survey Research Methods 6:37–48.

    Google Scholar 

  • Cieciuch, Jan, and Eldad Davidov. 2015. Establishing measurement invariance across online and offline samples. A tutorial with the software packages Amos and Mplus. Studia Psychologica 15: 83–99. https://doi.org/10.21697/sp.2015.14.2.06

    Article  Google Scholar 

  • Cieciuch, Jan, and Shalom H. Schwartz. 2012. The number of distinct basic values and their structure assessed by PVQ-40. Journal of Personality Assessment 94:321–328. https://doi.org/10.1080/00223891.2012.655817

    Article  Google Scholar 

  • Cieciuch, Jan, Eldad Davidov and René Algesheimer. 2016. The stability and change of value structure and priorities in childhood: A longitudinal study. Social Development 25:503–527. https://doi.org/10.1111/sode.12147

    Article  Google Scholar 

  • Cieciuch, Jan, Eldad Davidov, Peter Schmidt, René Algesheimer and Shalom H. Schwartz. 2014. Comparing results of an exact versus an approximate (Bayesian) measurement invariance test: A cross-country illustration with a new scale to measure 19 human values. Frontiers in Psychology 982:1–10. https://doi.org/10.3389/fpsyg.2014.00982

    Article  Google Scholar 

  • Cieciuch, Jan, Eldad Davidov and Peter Schmidt. 2018. Using alignment optimization in establishing measurement invariance. In Cross-cultural analysis: Methods and applications, 2nd edition, eds. Eldad Davidov, Peter Schmidt, Jaak Billiet and Bart Meuleman. New York: Routledge Taylor & Francis Group.

    Google Scholar 

  • Cieciuch, Jan, Eldad Davidov, Michele Vecchione, Constanze Beierlein and Shalom H. Schwartz. 2014a. The cross-national invariance properties of a new scale to measure 19 basic human values. A test across eight countries. Journal of Cross-Cultural Psychology 45:764–779. https://doi.org/10.1177/0022022114527348

    Article  Google Scholar 

  • Cieciuch, Jan, Eldad Davidov, Michele Vecchione and Shalom H. Schwartz. 2014b. A hierarchical structure of basic human values in a third-order confirmatory factor analysis. Swiss Journal of Psychology 73:177–182. https://doi.org/10.1024/1421-0185/a000134

    Article  Google Scholar 

  • Cieciuch, Jan, Eldad Davidov, René Algesheimer and Peter Schmidt. 2017. Testing for approximate measurement invariance of human values in the European Social Survey. Sociological Methods & Research. https://doi.org/10.1177/0049124117701478

    Article  Google Scholar 

  • Cieciuch, Jan, Shalom H. Schwartz and Eldad Davidov. 2015. Values, social psychology of. In International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, v. 25, ed. James D. Wright, 41–46. Oxford: Elsevier.

    Chapter  Google Scholar 

  • Cieciuch, Jan, Shalom H. Schwartz and Michele Vecchione. 2013. Applying the refined values theory to past data: What can researchers gain? Journal of Cross-Cultural Psychology 44:1215–1234. https://doi.org/10.1177/0022022113487076

    Article  Google Scholar 

  • Coromina, Lluis, and Eldad Davidov. 2013. Evaluating measurement invariance for social and political trust in Western Europe over four measurement time points (2002–2008). ASK Research & Methods 22:35–52.

    Google Scholar 

  • Davidov, Eldad. 2008. A cross-country and cross-time comparison of the human values measurements with the second round of the European Social Survey. Survey Research Methods 2:33–46.

    Google Scholar 

  • Davidov, Eldad. 2009. Measurement equivalence of nationalism and constructive patriotism in the ISSP: 34 countries in a comparative perspective. Political Analysis 17:64–82.

    Article  Google Scholar 

  • Davidov, Eldad. 2010. Testing for comparability of human values across countries and time with the third round of the European Social Survey. International Journal of Comparative Sociology 51:171–191. https://doi.org/10.1177/0020715210363534

    Article  Google Scholar 

  • Davidov, Eldad, and Pascal Siegers. 2010. Comparing basic human values in East and West Germany. In Komparative empirische Sozialforschung (Comparative empirical social research), eds. Tilo Beckers, Klaus Birkelbach, Jörg Hagenah, and Ulrich Rosar, 43–63. Wiesbaden: VS.

    Chapter  Google Scholar 

  • Davidov, Eldad, Jan Cieciuch, Peter Schmidt, Bart Meuleman and René Algesheimer. 2015. The comparability of measurements of attitudes toward immigration in the European Social Survey: Exact versus approximate measurement equivalence. Public Opinion Quarterly 79: 244–266. https://doi.org/10.1093/poq/nfv008

    Article  Google Scholar 

  • Davidov, Eldad, Hermann Dülmer, Jan Cieciuch, Anabel Kuntz, Daniel Seddig and Peter Schmidt 2016. Explaining measurement nonequivalence using multilevel structural equation modeling: The case of attitudes toward citizenship rights. Sociological Methods & Research. https://doi.org/10.1177/0049124116672678

    Article  Google Scholar 

  • Davidov, Eldad, Hermann Dülmer, Elmar Schlueter, Peter Schmidt and Bart Meuleman. 2012. Using a multilevel structural equation modeling approach to explain cross-cultural measurement noninvariance. Journal of Cross-Cultural Psychology 43:558–575. https://doi.org/10.1177/0022022112438397

    Article  Google Scholar 

  • Davidov, Eldad, Bart Meuleman, Jan Cieciuch, Peter Schmidt and Jaak Billiet. 2014. Measurement equivalence in cross-national research. Annual Review of Sociology 40:55–75. https://doi.org/10.1146/annurev-soc-071913-043137

    Article  Google Scholar 

  • Davidov, Eldad, Peter Schmidt and Shalom H. Schwartz. 2008. Bringing values back in: The adequacy of the European Social Survey to measure values in 20 countries. Public Opinion Quarterly 72:420–445. https://doi.org/10.1093/poq/nfn035

    Article  Google Scholar 

  • De Beuckelaer, Alain, and Gilbert Swinnen. 2018. Biased latent variable mean comparisons due to measurement noninvariance: A simulation study. In Cross-cultural research: Methods and applications, 2nd edition, eds. Eldad Davidov, Peter Schmidt, Jaak Billiet and Bart Meuleman, 127–156. New York: Routledge Taylor & Francis Group.

    Chapter  Google Scholar 

  • Döring, Anna, Shalom H. Schwartz, Jan Cieciuch, Patrick J. F. Groenen, Valentina Glatzel, Justyna Harasimczuk, Nicole Janowicz, Maya Nyagolova, Rebecca E. Scheefer, Matthias Allritz, Taciano L. Milfont and Wolfgang Bilsky. 2015. Cross-cultural evidence of value structures and priorities in childhood. British Journal of Psychology 106:675–699. https://doi.org/10.1111/bjop.12116

    Article  Google Scholar 

  • Durkheim, Émile. 1897/1964. Suicide. Glencoe, IL: Free Press.

    Google Scholar 

  • Goerres, Achim, Markus B. Siewert and Claudius Wagemann. 2019. Internationally comparative research designs in the social sciences: Fundamental issues, case selection logics, and research limitations. In Cross-national comparative research – analytical strategies, results and explanations. Sonderheft Kölner Zeitschrift für Soziologie und Sozialpsychologie. Eds. Hans-Jürgen Andreß, Detlef Fetchenhauer and Heiner Meulemann. Wiesbaden: Springer VS. https://doi.org/10.1007/s11577-019-00600-2.

  • Guenole, Nigel. 2016. The importance of isomorphism for conclusions about homology: A Bayesian multilevel structural equation modeling approach with ordinal indicators. Frontiers in Psychology 7:289. https://doi.org/10.3389/fpsyg.2016.00289

    Article  Google Scholar 

  • Hitlin, Steven, and Allyn Piliavin. 2004. Values: Reviving a dormant concept. Annual Review of Sociology 30:359–393. https://doi.org/10.1146/annurev.soc.30.012703.110640

    Article  Google Scholar 

  • Hofstede, Geert. 2000. Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations, 2nd edition. Beverly Hills, CA: Sage.

    Google Scholar 

  • Horn, John L., and John J. McArdle. 1992. A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research 18:117–144. https://doi.org/10.1080/03610739208253916

    Article  Google Scholar 

  • Inglehart, Ronald, and Wayne E. Baker. 2000. Modernization, cultural change, and the persistence of traditional values. American Sociological Review 65:19–51.

    Article  Google Scholar 

  • Jak, Suzanne, Frans J. Oort and Conor V. Dolan. 2013. A test for cluster bias: Detecting violations of measurement invariance across clusters in multilevel data. Structural Equation Modeling 20:265–282. https://doi.org/10.1080/10705511.2013.769392

    Article  Google Scholar 

  • Jöreskog, Karl G. 1971. Simultaneous factor analysis in several populations. Psychometrika 36:409–426. https://doi.org/10.1007/BF02291366

    Article  Google Scholar 

  • Kluckhohn, Clyde. 1951. Values and value-orientations in the theory of action: An exploration in definition and classification. In Toward a general theory of action, eds. Talcott Parsons and Edward A. Shils, 388–433. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Knoppen, Desirée, and Willem Saris. 2009. Do we have combine values in the Schwartz’ human values scale? A comment on the Davidov studies. Survey Research Methods 3:91–103.

    Google Scholar 

  • Lomazzi, Vera. 2018. Using alignment optimization to test the measurement invariance of gender role attitudes in 59 countries. Methods, data, analyses: A journal for quantitative methods and survey methodology (mda) 12:77–103. https://doi.org/10.12758/mda.2017.09

    Article  Google Scholar 

  • Magun, Vladimir, Maxim Rudnev and Peter Schmidt. 2016. Within- and between-country value diversity in Europe: A typological approach. European Sociological Review 32:189–202. https://doi.org/10.1093/esr/jcv080

    Article  Google Scholar 

  • Marsh, Herbert W., Jiesi Guo, Philip D. Parker, Benjamin Nagengast, Tihomir Asparouhov, Bengt O. Muthén and Theresa Dicke. 2017. What to do when scalar invariance fails: The extended alignment method to multi-group factor analysis comparison of latent means across many groups. Structural Equation Modeling. https://doi.org/10.1037/met0000113

    Article  Google Scholar 

  • Meitinger, Katharina. 2017. Necessary but insufficient: Why measurement invariance tests need online probing as a complementary tool. Public Opinion Quarterly 81:447–472. https://doi.org/10.1093/poq/nfx009.

    Article  Google Scholar 

  • Merkle, Edgar C., and Yves Rosseel. 2016. blavaan: Bayesian structural equation modelling via parameter expansion. arXiv: 1511.05604v2 [stat.CO]. Retrieved from https://arxiv.org/abs/1511.05604 on June 4, 2018.

    Google Scholar 

  • Meuleman, Bart. 2019. Multilevel structural equation modeling for cross-national comparative research. In Cross-national comparative research – analytical strategies, results and explanations. Sonderheft Kölner Zeitschrift für Soziologie und Sozialpsychologie. Eds. Hans-Jürgen Andreß, Detlef Fetchenhauer and Heiner Meulemann. Wiesbaden: Springer VS. https://doi.org/10.1007/s11577-019-00605-x.

  • Millsap, Roger E. 2011. Statistical approaches to measurement invariance. New York: Routledge.

    Google Scholar 

  • Munck, Ingrid, Carolyn Barner and Judith Torney-Purta. 2017. Measurement invariance in comparing attitudes toward immigrants among youth across Europe in 1999 and 2009. The alignment method applied to IEA CIVED and ICCS. Sociological Methods & Research. https://doi.org/10.1177/0049124117729691

    Article  Google Scholar 

  • Muthén Bengt O. 1994. Multilevel covariance structure analysis. Sociological Methods & Research 22:376–398. https://doi.org/10.1177/0049124194022003006

    Article  Google Scholar 

  • Muthén, Bengt O., and Tihomir Asparouhov. 2013. BSEM measurement invariance analysis. Mplus Web Notes 17:1–48.

    Google Scholar 

  • Muthén, Bengt O., and Tihomir Asparouhov. 2014. IRT studies of many groups: The alignment method. Frontiers in Psychology 978:1–7. https://doi.org/10.3389/fpsyg.2014.00978

    Article  Google Scholar 

  • Muthén, Bengt O., and Tihomir Asparouhov. 2017. Recent methods for the study of measurement invariance with many groups. Alignment and random effects. Sociological Methods & Research. https://doi.org/10.1177/0049124117701488

    Article  Google Scholar 

  • Muthén, Linda K., and Bengt O. Muthén. 1998–2014. Mplus user’s guide. Los Angeles: Muthén & Muthén.

    Google Scholar 

  • Oberski, Daniel L. 2014. Evaluating sensitivity of parameters of interest to measurement invariance in latent variable models. Political Analysis 22:45–60. https://doi.org/10.1093/pan/mpt014

    Article  Google Scholar 

  • Rokeach, Milton. 1973. The nature of human values. New York, NY: Free Press.

    Google Scholar 

  • Rudnev, Maksim, Ekaterina Lytkina, Eldad Davidov, Peter Schmidt and Andreas Zick. 2018a. Testing measurement invariance for a second-order factor: A cross-national test of the alienation scale. Methods, data, analyses: A journal for quantitative methods and survey methodology (mda) 12:47–76. https://doi.org/10.12758/mda.2017.11

    Article  Google Scholar 

  • Rudnev, Maxim, Vladimir Magun and Shalom Schwartz. 2018b. Relations among higher order values around the world. Journal of Cross-Cultural Psychology 49(8):1165–1182. https://doi.org/10.1177/0022022118782644

    Article  Google Scholar 

  • Ruelens, Anna, Bart Meuleman and Ides Nicaise. 2016. Examining measurement isomorphism of multilevel constructs: The case of political trust. Social Indicators Research. https://doi.org/10.1007/s11205-017-1799-6

    Article  Google Scholar 

  • Schafer, Joseph L., and John W. Graham. 2002. Missing values: Our view of the state of the art. Psychological Methods 7:147–177. https://doi.org/10.1037/1082-989X.7.2.147

    Article  Google Scholar 

  • Schmidt-Catran, Alexander W., Malcolm Fairbrother and Hans-Jürgen Andreß. 2019. Multilevel models for the analysis of comparative survey data: Common problems and some solutions. In Cross-national comparative research – analytical strategies, results and explanations. Sonderheft Kölner Zeitschrift für Soziologie und Sozialpsychologie. Eds. Hans-Jürgen Andreß, Detlef Fetchenhauer and Heiner Meulemann. Wiesbaden: Springer VS. https://doi.org/10.1007/s11577-019-00607-9.

  • Schwartz, Shalom H. 1992. Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. In Advances in experimental social psychology, vol. 25, ed. Mark Zanna, 1–65. London, UK: Academic Press.

    Google Scholar 

  • Schwartz, Shalom H. 2003. A proposal for measuring value orientations across nations. In Questionnaire development package of the European Social Survey, 259–319. Retrieved from www.europeansocialsurvey.org, June 30, 2016.

    Google Scholar 

  • Schwartz, Shalom H., and Jan Cieciuch. 2016. Values. In The ITC international handbook of testing and assessment, eds. Frederick T. L. Leong, Dave Bartram, Fanny M. Cheung, Kurt F. Geisinger and Dragos Iliescu, 106–119. Oxford: Oxford University Press.

    Google Scholar 

  • Schwartz, Shalom H., Jan Cieciuch, Michelle Vecchione, Eldad Davidov, Ronald Fischer, Constanze Beierlein, Alice Ramos, Markku Verkasalo, Jan-Erik Lönnqvist, Kursad Demirutku, Ozlem Dirilen-Gumus and Mark Konty. 2012. Refining the theory of basic individual values. Journal of Personality and Social Psychology 103:663–688. https://doi.org/10.1037/a0029393

    Article  Google Scholar 

  • Schwartz, Shalom H., Gila Melech, Arielle Lehmann, Steven Burgess, Mari Harris and Vicki Owens. 2001. Extending the cross-cultural validity of the theory of basic human values with a different method of measurement. Journal of Cross-Cultural Psychology 32:519–542.

    Article  Google Scholar 

  • Sokolov, Boris. 2018. The index of emancipative values: Measurement model Misspecifications. American Political Science Review 112:395–408.

    Article  Google Scholar 

  • Steenkamp, Jan-Benedict E. M., and Hans Baumgartner. 1998. Assessing measurement invariance in cross-national consumer research. Journal of Consumer Research 25:78–90. https://doi.org/10.1086/209528

    Article  Google Scholar 

  • Steinmetz, Holger. 2018. Estimation and comparison of latent means across cultures. In Cross-cultural analysis: Methods and applications, 2nd edition, eds. Eldad Davidov, Peter Schmidt, Jaak Billiet and Bart Meuleman, 95–126. New York: Routledge Taylor & Francis Group.

    Chapter  Google Scholar 

  • Steinmetz, Holger Rodrigo Isidor, Naissa Baeuerle. 2012. Testing the circular structure of human values: A meta-analytical structural equation modelling approach. Survey Research Methods 6:61–75

    Google Scholar 

  • van de Schoot, Rens, Anouck Kluytmans, Lars Tummers, Peter Lugtig, Joop Hox and Bengt O. Muthén. 2013. Facing off with Scylla and Charybdis: A comparison of scalar, partial, and the novel possibility of approximate measurement invariance. Frontiers in Psychology 770:1–15. https://doi.org/10.3389/fpsyg.2013.00770

    Article  Google Scholar 

  • Vandenberg, Robert J., and Charles E. Lance. 2000. A review and synthesis of the measurement invariance literature: Suggestions, practices and recommendations for organizational research. Organizational Research Methods 3:4–69. https://doi.org/10.1177/109442810031002

    Article  Google Scholar 

  • Weber, Max. 1905/1958. The protestant ethic and the spirit of capitalism. New York: Scribner’s.

    Google Scholar 

  • Welzel, Christian, and Ronald F. Inglehart. 2016. Misconceptions of measurement equivalence: Time for a paradigm shift. Comparative Political Studies 49:1068–1094.

    Article  Google Scholar 

  • Zercher, Florian, Peter Schmidt, Jan Cieciuch and Eldad Davidov. 2015. The comparability of the universalism value over time and across countries in the European Social Survey: Exact versus approximate measurement invariance. Frontiers in Psychology 733:1–11. https://doi.org/10.3389/fpsyg.2015.00733

    Article  Google Scholar 

Download references

Acknowledgements

The work of the first, second and fourth authors was supported by the University Research Priority Program Social Networks of the University of Zurich. The work of the third author was supported by the Alexander von Humboldt Polish Honorary Research Fellowship granted by the Foundation for Polish Science for the international cooperation between Peter Schmidt and Jan Cieciuch. The authors would like to thank Lisa Trierweiler and Neil Mussett for the English proof of the manuscript.

Author information

Authors and Affiliations

  1. Institute of Psychology, Cardinal Wyszyński University in Warsaw, Wóycickiego 1/3 bud. 14, 01-938, Warsaw, Poland

    Jan Cieciuch

  2. Institut für Soziologie und Sozialpsychologie, Universität zu Köln, Albertus-Magnus-Platz, 50923, Cologne, Germany

    Eldad Davidov

  3. Department of Sociology and University Research Priority Program Social Networks, University of Zurich, Andreasstrasse 15, 8050, Zurich, Switzerland

    Eldad Davidov

  4. Center for International Development and Environmental Research (ZEU), University of Giessen, Senckenbergstr. 3, 35390, Giessen, Germany

    Peter Schmidt

  5. Department of Business Administration and University Research Priority Program Social Networks, University of Zurich, Andreasstrasse 15, 8050, Zurich, Switzerland

    Jan Cieciuch & René Algesheimer

Authors
  1. Jan Cieciuch
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eldad Davidov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Peter Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. René Algesheimer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eldad Davidov.

Appendix

Appendix

 

Table 5 Importance of conservation values: Country rankings across all European Social Survey (ESS) rounds (The value means estimated by the alignment optimization are in parentheses.). (Author’s own work)
Full size table
Table 6 Importance of self-transcendence values: Country rankings across all European Social Survey (ESS) rounds (The value means estimated by the alignment optimization are in parentheses). (Author’s own work)
Full size table
Table 7 Importance of self-enhancement values: Country rankings across all European Social Survey (ESS) (The value means estimated by the alignment optimization are in parentheses). (Author’s own work)
Full size table
Table 8 Importance of openness to change values (without hedonism): Country rankings across all European Social Survey (ESS) rounds (The value means estimated by the alignment optimization are in parentheses). (Author’s own work)
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cieciuch, J., Davidov, E., Schmidt, P. et al. How to Obtain Comparable Measures for Cross-National Comparisons. Köln Z Soziol 71 (Suppl 1), 157–186 (2019). https://doi.org/10.1007/s11577-019-00598-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11577-019-00598-7

Keywords

Schlüsselwörter

Search

Navigation