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New Life for Old Ideas: The "Second Wave" of Sequence Analysis Bringing the "Course" Back Into the Life Course

Author

Listed:
  • Silke Aisenbrey

    (Yeshiva University, New York, NY, USA)

  • Anette E. Fasang

    (Yale University, New Haven, CT, USA, anette.fasang@yale.edu)

Abstract

In this article the authors draw attention to the most recent and promising developments of sequence analysis. Taking methodological developments in life course sociology as the starting point, the authors detail the complementary strength in sequence analysis in this field. They argue that recent advantages of sequence analysis were developed in response to criticism of the original work, particularly optimal matching analysis. This debate arose over the past two decades and culminated in the 2000 exchange in Sociological Methods & Research. The debate triggered a "second wave" of sequence techniques that led to new technical implementations of old ideas in sequence analysis. The authors bring these new technical approaches together, demonstrate selected advances with synthetic example data, and show how they conceptually contribute to life course research. This article demonstrates that in less than a decade, the field has made much progress toward fulfilling the prediction that Andrew Abbott made in 2000, that "anybody who believes that pattern search techniques are not going to be basic to social sciences over the next 25 years is going to be very much surprised" (p. 75).

Suggested Citation

  • Silke Aisenbrey & Anette E. Fasang, 2010. "New Life for Old Ideas: The "Second Wave" of Sequence Analysis Bringing the "Course" Back Into the Life Course," Sociological Methods & Research, , vol. 38(3), pages 420-462, February.
  • Handle: RePEc:sae:somere:v:38:y:2010:i:3:p:420-462
    DOI: 10.1177/0049124109357532
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    References listed on IDEAS

    as
    1. Francesco Billari & Raffaella Piccarreta, 2005. "Analyzing Demographic Life Courses through Sequence Analysis," Mathematical Population Studies, Taylor & Francis Journals, vol. 12(2), pages 81-106.
    2. Francesco C. Billari & Johannes Fürnkranz & Alexia Prskawetz, 2006. "Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach," European Journal of Population, Springer;European Association for Population Studies, vol. 22(1), pages 37-65, March.
    3. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    4. Andrew Abbott, 1990. "A Primer on Sequence Methods," Organization Science, INFORMS, vol. 1(4), pages 375-392, November.
    5. Christian Brzinsky-Fay & Ulrich Kohler & Magdalena Luniak, 2006. "Sequence analysis with Stata," Stata Journal, StataCorp LP, vol. 6(4), pages 435-460, December.
    6. Arnstein Aassve & Francesco C. Billari & Raffaella Piccarreta, 2007. "Strings of Adulthood: A Sequence Analysis of Young British Women’s Work-Family Trajectories," European Journal of Population, Springer;European Association for Population Studies, vol. 23(3), pages 369-388, October.
    7. Laurent Lesnard, 2006. "Optimal Matching and Social Sciences," Working Papers 2006-01, Center for Research in Economics and Statistics.
    8. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
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