Skip to main content

Recent Developments in Structural Equation Modeling with Panel Data

Causal Analysis and Change over Time in Attitude Research

  • Chapter
  • First Online:
Einstellungen und Verhalten in der empirischen Sozialforschung

Zusammenfassung

This article outlines the various applications of longitudinal models using the structural equation modeling (SEM) framework. Two classical approaches of longitudinal analysis in SEM are the autoregressive cross-lagged models and the latent growth curve models. Hybrid longitudinal models in SEM attempt to combine the two strands of techniques. Recently, these hybrid models have been expanded upon to properly separate between- and within-effects. This article demonstrates the application of these models by empirically examining the relationship between environmental values and attitudes towards the so-called Energy Transition in Germany over time. We show that a variety of research questions can be examined using longitudinal models in SEM. The new developments in longitudinal models in SEM furthermore make it possible for researchers to more accurately test theories.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 49.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur

  • Berry, D., and M. Willoughby. 2017. On the Practical Interpretability of Cross-Lagged Panel Models: Rethinking a Developmental Workhorse. Child Development 88(4): 1186–1206.

    Google Scholar 

  • Best, H., and T. Dannwolf 2014: Environmental Attitudes and Behavior. In: GESIS Panel – Standard Edition. Köln.

    Google Scholar 

  • Best, H., and J. Mayerl. 2013. Values, Beliefs, Attitudes: An Empirical Study on the Structure of Environmental Concern and Recycling Participation. Social Science Quarterly 94(3): 691-714.

    Google Scholar 

  • Bianconcini, S. and K. Bollen. 2018. The Latent Variable-Autoregressive Latent Trajectory Model: A General Framework for Longitudinal Analysis. Structural Equation Modeling: A Multidisciplinary Journal 00: 1-18.

    Google Scholar 

  • Biesanz, J. 2012. Autoregressive Longitudinal Models. In Handbook of Structural Equation Modeling, Ed. R. Hoyle, 459-471. New York, London: The Guilford Press.

    Google Scholar 

  • Bollen, K., and J. Brand. 2010. A General Panel Model with Random and Fixed Effects: A Structural Equations Approach. Social Forces 89(1): 1-34.

    Google Scholar 

  • Curran, P., and K. Bollen. 2001. The Best of Both Worlds. Combining Autoregressive and Latent Curve Models. In New Methods for the Analysis of Change, Eds. L. M. Collins and A. G. Sayer, 107-135. Washington: American Psychological Association.

    Google Scholar 

  • Curran, P., A. Howard, S. Bainter, S. Lane, and S. McGinley. 2014. The Separation of Between-Person and Within-Person Components of Individual Change Over Time: A Latent Curve Model With Structured Residuals. Journal of Consulting and Clinical Psychology 82(5): 879-894.

    Google Scholar 

  • Dunlap, R., K. Van Liere, A. Mertig, and R. Jones. 2000. Measuring Endorsement of the New Ecological Paradigm: A Revised NEP Scale. Journal of Social Issues 56(3): 425-442.

    Google Scholar 

  • Eagly, A., and S. Chaiken. 1998. Attitude structure and function. In The Handbook of social psychology Eds. D. T. Gilbert, S. T. Fiske, and G. Lindzey, 269-322. New York: McGraw-Hill.

    Google Scholar 

  • Ferrer, E., N. Balluerka, and K. Widaman. 2008. Factorial Invariance and the Specification of Second-Order Latent Growth Models. Methodology 4(1): 22-36.

    Google Scholar 

  • Finkel, Stevens E. 1995. Causal analysis with panel data. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Fishbein, Martin, and I. Ajzen. 2010. Predicting and Changing Behavior. New York, Hove: Psychology Press.

    Google Scholar 

  • GESIS. 2016. GESIS Panel Extended Edition. GESIS Data Archive, Cologne. ZA5664 Datafile Version 17.0.0. https://doi.org/10.4232/1.12742.

  • Granger, W. J. 1969. Investigating Causal Relations by Econometric Models and Cross-Spectral Methods. Econometrica 37(3): 424-438.

    Google Scholar 

  • Hair, Joseph F., W. Black, B. Babin, and R. Anderson. 2010. Multivariate Data Analysis (7th Ed.). Upper Saddle River, NJ: Pearson.

    Google Scholar 

  • Hamaker, E., R. Kuiper, and R. Grasman. 2015. A Critique of the Cross-Lagged Panel Model. Psychological Methods 20(1): 102-116.

    Google Scholar 

  • Hoffmann, L. and R. Stawski. 2009. Persons as Contexts: Evaluating Between-Person and Within-Person Effects in Longitudinal Analysis. Research in Human Development 6(2-3): 97-120.

    Google Scholar 

  • Keijsers, L. 2016. Parental monitoring and adolescent problem behaviors: How much do we really know? International Journal of Behavioral Development 40(3): 271-281.

    Google Scholar 

  • Kline, Rex. 2011. Principles and Practice of Structural Equation Modeling. Fourth Edition. New York, London: The Guilford Press.

    Google Scholar 

  • Krause, T., and D. Urban. 2013. Panelanalyse mit Mehrebenenmodellen. Eine anwendungsorientierte Einführung. Schriftenreihe des Instituts für Sozialwissenschaften der Universität Stuttgart. https://doi.org/10.18419/opus-5649

  • Mayerl, J. 2016. Environmental Concern in Cross-National Comparison – Methodological Threats and Measurement Equivalence. In Green European: Environmental Behaviour and Attitudes in Europe in a Historical and Cross-Cultural Comparative Perspective, Eds. A. Telesience, and M. Groß, 182-204. London, New York: Routledge.

    Google Scholar 

  • Opp, K.-D. 2010. Kausalität als Gegenstand der Sozialwissenschaften und der multivariaten Statistik. In Handbuch der sozialwissenschaftlichen Datenanalyse, Eds. C. Wolf and H. Best, 9-38. Wiesbaden: VS Verlag für Sozialwissenschaften.

    Google Scholar 

  • Rokeach, M. 1968. A Theory of Organization and Change Within Attitude Systems. Journal of Social Issues 24(1): 13-33.

    Google Scholar 

  • Schlüter, E., E. Davidov, and P. Schmidt. 2007. Applying Autoregressive Cross-Lagged and Latent Growth Curve Models to a Three-Wave Panel Study. In Longitudinal models in the behavior and related sciences, Eds. K. van Montfort, J. Oud and A. Satorra, 315-336. Mahwah, New Jersey: Lawrence Erlbaum Publishers, EAM Book Series.

    Google Scholar 

  • Schwartz, S. 2012. An Overview of the Schwartz Theory of Basic Values. Online Readings in Psychology and Culture 2(1). https://doi.org/10.9707/2307-0919.1116.

  • Stern, P., and T. Dietz. 1994. The value basis of environmental concern. Journal of Social Issues 50(3): 65-84.

    Google Scholar 

  • Stern, P., T. Dietz, L. Kalof, and G. Guagnano. 1995. Values, beliefs and proenvironmental action: Attitude formation towards emergent attitude objects. Journal of Applied Social Psychology 25: 1611–1636.

    Google Scholar 

  • Urban, D. 2002. Prozessanalyse im Strukturgleichungsmodell. Zur Anwendung latenter Wachstumskurvenmodelle in der Sozialisationsforschung. ZA-Information/Zentralarchiv für Empirische Sozialforschung 51: 6-37.

    Google Scholar 

  • Urban, Dieter. 2004. Neue Methoden der Längsschnittanalyse. Zur Anwendung von latenten Wachstumskurvenmodellen in Einstellungs- und Sozialisationsforschung. Münster: Lit Verlag.

    Google Scholar 

  • Urban, Dieter, and J. Mayerl. 2011. Regressionsanalyse: Theorie, Technik und Anwendung. 4., überarbeitete und erweiterte Auflage. Wiesbaden: VS Verlag für Sozialwissenschaften.

    Google Scholar 

  • Urban, Dieter, and J. Mayerl. 2014. Strukturgleichungsmodellierung: Ein Ratgeber für die Praxis. Wiesbaden: Springer VS Verlag.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jochen Mayerl .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Mayerl, J., Andersen, H. (2019). Recent Developments in Structural Equation Modeling with Panel Data. In: Mayerl, J., Krause, T., Wahl, A., Wuketich, M. (eds) Einstellungen und Verhalten in der empirischen Sozialforschung . Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-16348-8_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-16348-8_17

  • Published:

  • Publisher Name: Springer VS, Wiesbaden

  • Print ISBN: 978-3-658-16347-1

  • Online ISBN: 978-3-658-16348-8

  • eBook Packages: Social Science and Law (German Language)

Publish with us

Policies and ethics