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Confounding True and Random Changes in Categorical Panel Data

Regression to the mean and Regression to the mode

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Lebensbedingungen in Deutschland in der Längsschnittperspektive

Zusammenfassung

The main advantage of panel analysis is that changes can be investigated at the individual level. However, the observed individual changes result not only from underlying, true changes but also from random fluctuations. The problem is that these random fluctuations may lead to systematically looking patterns of change that seemingly beg for substantive, theoretical explanations. Notorious in this respect is the regression to the mean phenomenon that has misled investigators everywhere and in all times. This phenomenon is more aptly called regression to the mode and in this latter form also affects the observed changes in categorical panel data. Latent class models are excellently suited to find out about the regression to the mode and prevent misleading explanations of panel data.

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Literatur

  • Andreß, Hans-Jürgen, J.A. Hagenaars, and S. Kühnel. 1997. Analyse von Tabellen und kategorialen Daten; Log-Lineare Modelle, latente Klasseanalyse, logistische Regression und GSK Ansatz. Berlin: Springer.

    Google Scholar 

  • Andreß, Hans-Jürgen, K. Golsch, and A.W. Schmidt. 2013. Applied Panel Data Analysis for Economic and Social Surveys. Heidelberg: Springer.

    Google Scholar 

  • Bassi, F., J.A. Hagenaars, M. Croon, and J.K. Vermunt. 2000. Estimating true changes when categorical panel data are affected by uncorrelated and correlated errors. Sociological Methods and Research 29: 230-268.

    Google Scholar 

  • Biemer, Paul P. 2011. Latent Class Analysis of Survey Error. Hoboken: Wiley.

    Google Scholar 

  • Campbell, Donald T., and D.A. Kenny. 1999. A primer on Regression Artifacts. New York: Guilford Press.

    Google Scholar 

  • Campbell, Donald T., and J.C. Stanley. 1966. Experimental and Quasi-Experimental Designs for Research. Chicago: Rand McNally.

    Google Scholar 

  • Clogg, C. C. 1981. Latent structure models of mobility. American Journal of Sociology 86:836-868.

    Google Scholar 

  • Das, P., and P.G.H. Mulder. 1983. Regression to the mode. Statistica Neerlandica 37: 15-20.

    Google Scholar 

  • Galton, Francis G. 1889. Natural Inheritance. London: Macmillan.

    Google Scholar 

  • Hagenaars, J.A. 1988. Latent structure models with direct effects between indicators: local dependence models. Sociological Methods and Research 16: 379-405.

    Google Scholar 

  • Hagenaars, Jacques A. 1990. Categorical Longitudinal Data; Log-linear Panel, Trend, and Cohort Analysis. Newbury Park, CA: Sage.

    Google Scholar 

  • Hagenaars, Jacques A. 2002. Directed loglinear modeling with latent variables: causal models for categorical data with nonsystematic and systematic measurement error. In Applied Latent Class Analysis, Eds. J.A. Hagenaars and A.L. McCutcheon, 234-286. New York: Cambridge University Press.

    Google Scholar 

  • Hagenaars, Jacques A. 2005. Misclassification phenomena in categorical data analysis: Regression toward the mean and tendency toward the mode. In New Developments in Categorical Data Analysis for the Social and Behavioral Sciences, Eds. A. van der Ark, M.A. Croon, and K. Sijtsma, 15-39. London: Lawrence Erlbaum.

    Google Scholar 

  • Hagenaars, Jacques A., and A.L. McCutcheon, Eds. 2002. Applied Latent Class Analysis. New York: Cambridge University Press.

    Google Scholar 

  • Hand, David J. 2014. The Improbability Principle; Why Coincidences, Miracles, and Rare Events Happen Every Day. New York: Scientific American/Farrar, Strauss and Giroux.

    Google Scholar 

  • Kendall, Patricia. 1954. Conflict and Mood; Factors Affecting Stability of Responses. Glencoe, IL: Free Press.

    Google Scholar 

  • Kendall, Patricia. 1972. The nature and determinants of turnover. In Continuities in the Language of Social Research, Eds. P. F. Lazarsfeld, A.K. Pasanella, and M. Rosenberg, 342-350. New York: Free Press.

    Google Scholar 

  • Langeheine, R., and F. Van de Pol. 2002. Latent markov chain. In Applied Latent Class Analysis, Eds. J.A. Hagenaars and A.L. McCutcheon, 304-341. New York: Cambridge University Press.

    Google Scholar 

  • Lazarsfeld, Paul F. 1972. The problem of measuring turnover. In Continuities in the Language of Social Research, Eds. P. F. Lazarsfeld, A. K. Pasanella, and M. Rosenberg, 358-367. New York: Free Press.

    Google Scholar 

  • Lord, Frederic M., and M.R. Novick. 1968. Statistical Theories of Mental Test Scores. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Maccoby, E.E. 1956. Pitfalls in the analysis of panel data; a research note on some technical aspects of Voting. American Journal of Sociology, 61: 359-362.

    Google Scholar 

  • Reichardt, C. S. 1999. Foreword. In A primer on regression artifacts, D. T. Campbell and D. A. Kenny, ix-xi. New York: Guilford Press.

    Google Scholar 

  • Shadish, W.R., Th.D. Cook, and D.T. Campbell. 2002. Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin.

    Google Scholar 

  • Stigler, Stephen M. 1999. Statistics on the Table; The History of Statistical Concepts and Methods. Cambridge: Harvard University Press.

    Google Scholar 

  • Stigler, Stephen M. 2016. The Seven Pillars of Statistical Wisdom. Cambridge: Harvard University Press.

    Google Scholar 

  • Suttcliffe, J. P. 1965a. A probability model for errors of classification; I: General considerations. Psychometrika, 30: 73-96.

    Google Scholar 

  • Suttcliffe, J.P. 1965b. A probability model for errors of classification; II: Particular Cases. Psychometrika, 30: 129-155.

    Google Scholar 

  • Thorndike, R.L. 1942. Regression fallacies in the matched group experiments. Psychometrika. 7: 85-102.

    Google Scholar 

  • Van der Heijden, P. G. M., L.A. Van der Ark, and A. Mooijaart. 2002. Some examples of latent budget analysis and its extensions. In Applied Latent Class Analysis, Eds. J. A. Hagenaars and A. L. McCutcheon, 107-136. New York: Cambridge University Press.

    Google Scholar 

  • Vermunt, Jeroen K. 1997. Loglinear Models for Event History Analysis. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Vermunt, Jeroen K. 2002. A general latent class approach to unobserved heterogeneity in the analysis of event history data. In Applied Latent Class Analysis, Eds. J.A. Hagenaars and A.L. McCutcheon, 383-407. New York: Cambridge University Press.

    Google Scholar 

  • Zeisel, Hans. 1968. Say it with Figures. New York: Harper and Row.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Tilburg, Niederlande

    Jacques A. Hagenaars

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  1. Jacques A. Hagenaars
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Correspondence to Jacques A. Hagenaars .

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Editors and Affiliations

  1. SOEP, DIW Berlin, Berlin, Germany

    Marco Giesselmann

  2. FB Kultur- und Sozialwissenschaften, Universität Osnabrück, Osnabrück, Niedersachsen, Germany

    Katrin Golsch

  3. Fachbereich Sozialökonomie, Universität Hamburg, Hamburg, Germany

    Henning Lohmann

  4. Universität zu Köln, Köln, Germany

    Alexander Schmidt-Catran

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Hagenaars, J.A. (2018). Confounding True and Random Changes in Categorical Panel Data. In: Giesselmann, M., Golsch, K., Lohmann, H., Schmidt-Catran, A. (eds) Lebensbedingungen in Deutschland in der Längsschnittperspektive. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-19206-8_14

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  • DOI: https://doi.org/10.1007/978-3-658-19206-8_14

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  • Publisher Name: Springer VS, Wiesbaden

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  • Online ISBN: 978-3-658-19206-8

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