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Sequence analysis using Stata

Author

Listed:
  • Christian Brzinsky-Fay

    (WZB)

  • Ulrich Kohler

    (WZB)

Abstract

Sequences are ordered lists of elements. A typical example is the sequence of bases in DNA. Other examples are sequences of employment stages during a lifetime or individual party preferences over time. Sequence analysis include techniques to handle, describe, and, most importantly, compare sequences. Sequences are most commonly used by geneticists but not as commonly by social scientists. This disparity is surprising, as sequence data are readily available for the social sciences. In fact, all data from panel studies can be regarded as sequence data. Nevertheless, social scientists relatively seldom use panel data for sequence analysis. The first aim of the presentation therefore is to illustrate a typical research topic that can be dealt with sequence analysis. The second part will then describe a bundle of user-written Stata programs for sequence analysis, including a Mata algorithm for performing optimal matching with the so-called Needleman–Wunsch algorithm.

Suggested Citation

  • Christian Brzinsky-Fay & Ulrich Kohler, 2006. "Sequence analysis using Stata," German Stata Users' Group Meetings 2006 07, Stata Users Group.
    • Handle: RePEc:boc:dsug06:07
    as

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    Cited by:

    1. Christian Brzinsky-Fay & Ulrich Kohler, 2010. "New Developments in Sequence Analysis," Sociological Methods & Research, , vol. 38(3), pages 359-364, February.
    2. Matissa Hollister, 2009. "Is Optimal Matching Suboptimal?," Sociological Methods & Research, , vol. 38(2), pages 235-264, November.
    3. Okka Zimmermann & Nicole Hameister, 2019. "Stable cohabitational unions increase quality of life: Retrospective analysis of partnership histories also reveals gender differences," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(24), pages 657-692.

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