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Classifying life course trajectories: a comparison of latent class and sequence analysis

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  • Nicola Barban
  • Francesco C. Billari

Abstract

In this article we compare two techniques that are widely used in the analysis of life course trajectories, latent class analysis (LCA) and sequence analysis (SA). In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of the classification obtained via the two techniques using an actual dataset on the life course trajectories of young adults. Then, we adopt a simulation approach to measure the ability of these two methods to correctly classify groups of life course trajectories when specific forms of "random" variability are introduced within pre-specified classes in an artificial dataset. In order to do so, we introduce simulation operators that have a life course and/or observational meaning. Our results contribute on the one hand to outline the usefulness and robustness of findings based on the classification of life course trajectories through LCA and SA, on the other hand to illuminate the potential pitfalls of actual applications of these techniques.
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Suggested Citation

  • Nicola Barban & Francesco C. Billari, 2012. "Classifying life course trajectories: a comparison of latent class and sequence analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 61(5), pages 765-784, November.
  • Handle: RePEc:bla:jorssc:v:61:y:2012:i:5:p:765-784
    DOI: j.1467-9876.2012.01047.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-9876.2012.01047.x
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    References listed on IDEAS

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    1. Christian Brzinsky-Fay & Ulrich Kohler, 2010. "New Developments in Sequence Analysis," Sociological Methods & Research, , vol. 38(3), pages 359-364, February.
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    Cited by:

    1. Mark Hanly & Paul Clarke & Fiona Steele, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 793-808, June.
    2. Brienna Perelli-Harris & Laura Bernardi, 2015. "Exploring social norms around cohabitation: The life course, individualization, and culture," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(25), pages 701-732, October.
    3. repec:spr:soinre:v:136:y:2018:i:1:d:10.1007_s11205-016-1528-6 is not listed on IDEAS
    4. Mitrofanova, Ekaterina S. & Artamonova, Alyona V., 2016. "Studying Family Formation Trajectories’ Deinstitutionalization in Russia Using Sequence Analysis," MPRA Paper 82877, University Library of Munich, Germany.
    5. Maria Sironi & Nicola Barban & Roberto Impiacciatore, 2013. "The Role of Parental Social Class in the Transition to Adulthood: A Sequence Analysis Approach in Italy and the United States," Working Papers 059, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), UniversitĂ  Commerciale Luigi Bocconi.
    6. Hanly, Mark & Clarke, Paul & Steele, Fiona, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," LSE Research Online Documents on Economics 64896, London School of Economics and Political Science, LSE Library.
    7. repec:spr:soinre:v:135:y:2018:i:1:d:10.1007_s11205-016-1469-0 is not listed on IDEAS

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