Academic Journal
Using sequence and cluster analysis to characterize variables that unfold over time: implementation and practical considerations for epidemiologists.
| Τίτλος: | Using sequence and cluster analysis to characterize variables that unfold over time: implementation and practical considerations for epidemiologists. |
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| Συγγραφείς: | Pacca L; Department of Epidemiology and Biostatistics, University of California San Francisco, 550 16th St 2nd floor, San Francisco, CA 94158, United States., Dang KV; University of Southern California, School of Gerontology, 3715 Mcclintock Ave., University Park Campus, Los Angeles CA 90089, United States., Koenig L; Society of Family Planning, 757 East 20th Avenue, Suite 370-232 Denver, CO 80205, United States., Duarte CDP; Stanford University School of Medicine, Department of Epidemiology and Population Health, 1701 Page Mill Road, 2nd Floor, Palo Alto, CA 9430, United States., Gaye SA; Olympia, Washington State, United States., Harrati A; Kaiser Permanente Community and Social Health, 1800 Harrison St., 11th Floor, Oakland CA 94612, California., Vable AM; Washington University in St. Louis School of Public Health, 1 Brookings Drive, St. Louis, MO 63130.; Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, 490 Illinois St., San Francisco CA 94158, United States. |
| Πηγή: | American journal of epidemiology [Am J Epidemiol] 2026 Jun 03; Vol. 195 (6), pp. 1707-1718. |
| Τύπος έκδοσης: | Journal Article; Research Support, N.I.H., Extramural |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Oxford University Press Country of Publication: United States NLM ID: 7910653 Publication Model: Print Cited Medium: Internet ISSN: 1476-6256 (Electronic) Linking ISSN: 00029262 NLM ISO Abbreviation: Am J Epidemiol Subsets: MEDLINE |
| Imprint Name(s): | Publication: Cary, NC : Oxford University Press Original Publication: Baltimore, School of Hygiene and Public Health of Johns Hopkins Univ. |
| Ιατρικοί όροι (MeSH): | Cluster Analysis* , Clustering Algorithms* , Sequence Analysis* , Epidemiologic Methods*, Retirement/statistics & numerical data ; Humans ; Longitudinal Studies |
| Περίληψη: | Characterizing longitudinal trajectories of variables that unfold over time (eg, social, health, or environmental variables) is a persistent challenge, but can be accomplished with sequence and cluster analysis, data-driven approaches that can differentiate timing, order, and duration of events. We present practical guidance on implementing sequence and cluster analysis for epidemiologists with the goal of providing clear advice on decision points and tradeoffs. We introduce the three main steps of sequence and cluster analysis: (1) coding trajectories of ordered events (data cleaning); (2) measuring dissimilarity between trajectories (sequence analysis); and (3) grouping similar trajectories (cluster analysis). Each of these steps presents researchers with several decision points, such as data cleaning rules, options for evaluating sequence dissimilarity, and choices of clustering algorithms. After outlining each of the sequence analysis steps, we provide an applied example of sequence analysis in which we create and group transition-to-retirement trajectories from age 51 to 75 years for a sample of 9189 Health and Retirement Study participants using self-reported employment information, then estimate the association between transition-to-retirement groups and self-rated health. We seek to provide an initial guide for epidemiologists through analytic decisions and implementation challenges of sequence analysis as this approach is increasingly implemented and undergoes methodological advances. This article is part of a Special Collection on Methods in Social Epidemiology. (© The Author(s) 2025. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.) |
| Grant Information: | K99 AG086672 United States AG NIA NIH HHS; R01 AG074351 United States AG NIA NIH HHS; R01AG074351 National Institute of Aging/National Institute of Health |
| Contributed Indexing: | Keywords: clustering; lifecourse epidemiology; longitudinal trajectories; methodological guide; sequence analysis |
| Entry Date(s): | Date Created: 20250412 Date Completed: 20260605 Latest Revision: 20260629 |
| Update Code: | 20260629 |
| PubMed Central ID: | PMC12952161 |
| DOI: | 10.1093/aje/kwaf065 |
| PMID: | 40219634 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1476-6256 |
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| DOI: | 10.1093/aje/kwaf065 |