IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v50y2021i3p1321-1352.html
   My bibliography  Save this article

Some Methods for the Analysis of Event Sequence Data from Multiple Respondents

Author

Listed:
  • John Levi Martin
  • James P. Murphy

Abstract

The analysis of sequence data poses a great challenge; existing methods for the comparison of sequences take what theoretical grounding they have from other fields (most importantly, genetics). We argue that set theory provides a way of establishing the relations between sequences that has a natural application to the case in which the sequences are orderings of a set of events, all compatible with an underlying partial order shared by multiple respondents. We also examine the possibility that observed differences in sequence data come from a stochastic process in which some events are poorly ordered because respondents cannot discriminate between them. We show that such methods shed light on several quantities that have been of interest to researchers, such as the degree of consensus within a group as to ideal sequences, the degree of respondent accuracy in reporting, and the degree to which plans and reality coincide.

Suggested Citation

  • John Levi Martin & James P. Murphy, 2021. "Some Methods for the Analysis of Event Sequence Data from Multiple Respondents," Sociological Methods & Research, , vol. 50(3), pages 1321-1352, August.
    • Handle: RePEc:sae:somere:v:50:y:2021:i:3:p:1321-1352
    DOI: 10.1177/0049124118799387
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124118799387
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124118799387?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Matissa Hollister, 2009. "Is Optimal Matching Suboptimal?," Sociological Methods & Research, , vol. 38(2), pages 235-264, November.
    2. 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.
    3. Anthony Paik & Vernon Woodley, 2012. "Symbols and investments as signals: Courtship behaviors in adolescent sexual relationships," Rationality and Society, , vol. 24(1), pages 3-36, February.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luca Maria Pesando & Nicola Barban & Maria Sironi & Frank F. Furstenberg, 2021. "A Sequence‐Analysis Approach to the Study of the Transition to Adulthood in Low‐ and Middle‐Income Countries," Population and Development Review, The Population Council, Inc., vol. 47(3), pages 719-747, September.
    2. 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.
    3. 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.
    4. Nicola Barban, 2013. "Family Trajectories and Health: A Life Course Perspective [Trajectoires familiales et santé: une approche sous l’angle de parcours de vie]," European Journal of Population, Springer;European Association for Population Studies, vol. 29(4), pages 357-385, November.
    5. 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.
    6. 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.
    7. Julia 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.
    8. repec:jss:jstsof:40:i04 is not listed on IDEAS
    9. Babette Bühler & Katja Möhring & Andreas P. Weiland, 2022. "Assessing dissimilarity of employment history information from survey and administrative data using sequence analysis techniques," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4747-4774, December.
    10. Marc A. Scott & Kaushik Mohan & Jacques‐Antoine Gauthier, 2020. "Model‐based clustering and analysis of life history data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1231-1251, June.
    11. 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.
    12. Brian T. Pentland & Thorvald Hærem & Derek Hillison, 2011. "The (N)Ever-Changing World: Stability and Change in Organizational Routines," Organization Science, INFORMS, vol. 22(6), pages 1369-1383, December.
    13. Michal Engelman & Heide Jackson, 2019. "Gradual Change, Homeostasis, and Punctuated Equilibrium: Reconsidering Patterns of Health in Later Life," Demography, Springer;Population Association of America (PAA), vol. 56(6), pages 2323-2347, December.
    14. Arthur Kaboth & Lena Hünefeld & Ralf Himmelreicher, 2023. "Employment trajectories of workers in low-skilled jobs in Western Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-17, December.
    15. Madero-Cabib, Ignacio & Biehl, Andres, 2021. "Lifetime employment–coresidential trajectories and extended working life in Chile," The Journal of the Economics of Ageing, Elsevier, vol. 19(C).
    16. Sebastian Jäckle, 2023. "What Comes after Cabinet? Post-Cabinet Careers of German Regional Ministers between 1945 and 2014," Social Sciences, MDPI, vol. 12(11), pages 1-34, October.
    17. Zhelyazkova, N., 2014. "Discovering and explaining work-family strategies of parents in Luxembourg," MERIT Working Papers 2014-022, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    18. repec:osf:socarx:kj8d5_v1 is not listed on IDEAS
    19. Thomas King, 2013. "A framework for analysing social sequences," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 167-191, January.
    20. Struffolino, Emanuela & Studer, Matthias & Fasang, Anette Eva, 2016. "Gender, education, and family life courses in East and West Germany: Insights from new sequence analysis techniques," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29, pages 66-79.
    21. Tsubasa Ito & Shonosuke Sugasawa, 2023. "Grouped generalized estimating equations for longitudinal data analysis," Biometrics, The International Biometric Society, vol. 79(3), pages 1868-1879, September.
    22. Wen-Jui Han & Julia Shu-Huah Wang, 2022. "Changing Employment and Work Schedule Patterns over the 30 Working Years—A Sequential Cluster Analysis," IJERPH, MDPI, vol. 19(20), pages 1-20, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:50:y:2021:i:3:p:1321-1352. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.