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SADI: Sequence analysis tools for Stata

Author

Listed:
  • Brendan Halpin

    (University of Limerick)

Abstract

The SADI package provides tools for sequence analysis, which focuses on the similarity and dissimilarity between categorical time series such as life-course trajectories. SADI’s main components are tools to calculate intersequence distances using several different algorithms, including the optimal matching algorithm, but it also includes utilities to graph, summarize, and manage sequence data. It provides similar functionality to the R package TraMineR and the Stata package SQ but is substantially faster than the latter.

Suggested Citation

  • Brendan Halpin, 2017. "SADI: Sequence analysis tools for Stata," Stata Journal, StataCorp LP, vol. 17(3), pages 546-572, September.
    • Handle: RePEc:tsj:stataj:y:17:y:2017:i:3:p:546-572
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    Citations

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    Cited by:

    1. Zhang, Nan & Nazroo, James & Vanhoutte, Bram, 2021. "The relationship between rural to urban migration in China and risk of depression in later life: An investigation of life course effects," Social Science & Medicine, Elsevier, vol. 270(C).
    2. Júlia Mikolai & Hill Kulu, 2019. "Union dissolution and housing trajectories in Britain," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(7), pages 161-196.
    3. Chang Heon Lee & J. Leon Zhao, 2022. "Social media engagement and crowdfunding performance: The moderating role of product type and entrepreneurs' characteristics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(11), pages 1559-1578, November.
    4. Elisabeth Beusch & Arthur Soest, 2020. "Labour Market Trajectories of the Self-employed in the Netherlands," De Economist, Springer, vol. 168(1), pages 109-146, March.
    5. Morten Wahrendorf & Christian Deindl & Jinkook Lee & Drystan Phillips, 2023. "Life history data from the gateway to global ageing data platform: resources for studying life courses across Europe," European Journal of Ageing, Springer, vol. 20(1), pages 1-8, December.
    6. Zimmermann, Okka, 2022. "The impact of personality on timing and dynamics of partnership formation: A longitudinal approach a longitudinal approach," IU Discussion Papers - Social Sciences 4 (August 2022), IU International University of Applied Sciences.
    7. Barbara Zimmermann & Simon Seiler, 2019. "The Relationship between Educational Pathways and Occupational Outcomes at the Intersection of Gender and Social Origin," Social Inclusion, Cogitatio Press, vol. 7(3), pages 79-94.
    8. Sun, Huaping & Kporsu, Anthony Kwaku & Taghizadeh-Hesary, Farhad & Edziah, Bless Kofi, 2020. "Estimating environmental efficiency and convergence: 1980 to 2016," Energy, Elsevier, vol. 208(C).
    9. Annina Ropponen & Pontus Josefsson & Petri Böckerman & Karri Silventoinen & Jurgita Narusyte & Mo Wang & Pia Svedberg, 2022. "Sustainable Working Life Patterns in a Swedish Twin Cohort: Age-Related Sequences of Sickness Absence, Disability Pension, Unemployment, and Premature Death during Working Life," IJERPH, MDPI, vol. 19(17), pages 1-14, August.
    10. Liao, Tim F. & Bolano, Danilo & Brzinsky-Fay, Christian & Cornwell, Benjamin & Fasang, Anette Eva & Helske, Satu & Piccarreta, Raffaella & Raab, Marcel & Ritschard, Gilbert & Struffolino, Emanuela & S, 2022. "Sequence analysis: Its past, present, and future," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 107, pages 1-1.
    11. 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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