Abstract
This chapter introduces the sequence analysis methodological framework to study trajectories in a life course perspective and discusses its potential for occupational health research. Aside from a conceptual presentation of the main concepts, it also aims to provide general and practical recommendations on the main decisions to be made when using sequence analysis.
Regularly identified as one of the key approaches for life course analysis, sequence analysis aims to analyze trajectories described as a sequence of categorical states using a holistic perspective. It regroups methods ranging from visualization to explanatory methods and provides a comprehensive overview of the observed trajectories taken as a whole. This overview can then be used for various purposes, such as describing a set of entire trajectories, identifying relevant or atypical regularities, or contrasting these trajectories according to other key aspects such as gender or education level. This general introduction to sequence analysis is based on a simple illustrative study of work-related stress trajectories following a corporate restructuring in Switzerland.
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References
Abbott A (1990) Conception of time and events in social science methods: causal and narrative approaches. Hist Methods 23(4):140–150
Abbott A, Forrest J (1986) Optimal matching methods for historical sequences. J Interdiscip Hist 16:471–494
Aisenbrey S, Fasang AE (2010) New life for old ideas: the ‘second wave’ of sequence analysis bringing the ‘course’ back into the life course. Sociol Methods Res 38(3):430–462
Bernardi L, Huinink J, Settersten RA (2019) The life course cube: a tool for studying lives. Adv Life Course Res 41:100258. https://doi.org/10.1016/j.alcr.2018.11.004
Blossfeld H-P, Rohwer G (2002) Techniques of event history modeling, new approaches to causal analysis, 2nd edn. Lawrence Erlbaum, Mahwah
Brzinsky-Fay C, Kohler U, Luniak M (2006) Sequence analysis with Stata. Stata J 6(4):435–460
Buchmann MC, Kriesi I (2011) Transition to adulthood in Europe. Annu Rev Sociol 37(1):481–503. https://doi.org/10.1146/annurev-soc-081309-150212
Bürgin R, Ritschard G (2014) A decorated parallel coordinate plot for categorical longitudinal data. Am Stat 68(2):98–103. https://doi.org/10.1080/00031305.2014.887591
Checkoway H, Pearce NE, Kriebel D (2004) Research methods in occupational epidemiology. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195092424.001.0001
de Jong T, Wiezer N, de Weerd M, Nielsen K, Mattila-Holappa P, Mockałło Z (2016) The impact of restructuring on employee Well-being: a systematic review of longitudinal studies. Work & Stress 30(1):91–114. https://doi.org/10.1080/02678373.2015.1136710
Eisenberg-Guyot J, Peckham T, Andrea SB, Oddo V, Seixas N, Hajat A (2020) Life-course trajectories of employment quality and health in the U.S.: a multichannel sequence analysis. Soc Sci Med 264(November):113327. https://doi.org/10.1016/j.socscimed.2020.113327
Elder GH, Johnson MK, Crosnoe R (2003) The emergence and development of life course theory. In: Mortimer JT, Shanahan MJ (eds) Handbook of the life course, Handbooks of Sociology and Social Research. Springer U.S., pp 3–19. https://doi.org/10.1007/978-0-306-48247-2_1
Elzinga CH, Studer M (2015) Spell sequences, state proximities and distance metrics. Sociol Methods Res 44(1):3–47. https://doi.org/10.1177/0049124114540707
Fasang AE, Liao TF (2014) Visualizing sequences in the social sciences. Sociol Methods Res 43(4):643–676. https://doi.org/10.1177/0049124113506563
Gabadinho A, Ritschard G, Müller NS, Studer M (2011) Analyzing and visualizing state sequences in R with TraMineR. J Stat Softw 40(4):1–37. http://www.jstatsoft.org/v40/i04
Gauthier J-A, Bühlmann F, Blanchard P (2014) Introduction: sequence analysis in 2014. In: Blanchard P, Bühlmann F, Gauthier J-A (eds) Advances in sequence analysis: theory, method, applications, Life Course Research and Social Policies, vol 2. Springer, Heidelberg
Giudici F, Morselli D (2019) 20 years in the world of work: a study of (nonstandard) occupational trajectories and health. Soc Sci Med 224(March):138–148. https://doi.org/10.1016/j.socscimed.2019.02.002
Halpin B (2017) SADI: sequence analysis tools for Stata. Stata J 17(3):546–572(27). https://www.stata-journal.com/article.html?article=st0486
Hamming RW (1950) Error detecting and error correcting codes. Bell Syst Tech J 26(2):147–160
Karasek RA (1979) Job demands, job decision latitude, and mental strain: implications for job redesign. Adm Sci Q 24(2):285. https://doi.org/10.2307/2392498
Kieselbach T, Nielsen K, Triomphe CE (2010) Psychosocial risks and health effects of restructuring. Brussels: Investing in well-being at work: Addressing psychosocial risks in times of change
Kuh D, Ben-Shlomo Y, Lynch J, Hallqvist J, Power C (2003) Life course epidemiology. J Epidemiol Community Health 57(10):778–783. https://doi.org/10.1136/jech.57.10.778
Levenshtein V (1966) Binary codes capable of correcting deletions, insertions, and reversals. Soviet Phys Doklady 10:707–710
Liefbroer AC (2019) Methodological diversity in life course research: blessing or curse? Adv Life Course Res 41(September):100276. https://doi.org/10.1016/j.alcr.2019.04.006
Mayer KU (2009) New directions in life course research. Annu Rev Sociol 35:413–433. https://doi.org/10.1146/annurev.soc.34.040507.134619
McLeod CB, Reiff E, Maas E, Bültmann U (2018) Identifying return-to-work trajectories using sequence analysis in a cohort of workers with work-related musculoskeletal disorders. Scand J Work Environ Health 44(2):147–155. https://doi.org/10.5271/sjweh.3701
Orsholits D (2020) Modelling the dynamics of vulnerability with latent variable methods. PhD Thesis, University of Geneva
Piccarreta R, Studer M (2019) Holistic analysis of the life course: methodological challenges and new perspectives. Adv Life Course Res 41:100251. https://doi.org/10.1016/j.alcr.2018.10.004
Scherer S (2001) Early career patterns: a comparison of Great Britain and West Germany. Eur Sociol Rev 17(2):119–144
Shanahan MJ (2000) Pathways to adulthood in changing societies: variability and mechanisms in life course perspective. Annu Rev Sociol 26:667–692. http://www.jstor.org/stable/223461
Spini D, Bernardi L, Oris M (2017) Toward a life course framework for studying vulnerability. Res Hum Dev 14(1):5–25. https://doi.org/10.1080/15427609.2016.1268892
Studer M (2013) WeightedCluster Library manual: a practical guide to creating typologies of trajectories in the social sciences with R, LIVES working papers 24. NCCR LIVES, Switzerland. https://doi.org/10.12682/lives.2296-1658.2013.24
Studer M (2021) Validating sequence analysis typologies using parametric bootstrap. Sociol Methodol 51(2):290–318. https://doi.org/10.1177/00811750211014232
Studer M, Ritschard G (2016) What matters in differences between life trajectories: a comparative review of sequence dissimilarity measures. J R Stat Soc Ser A 179(2):481–511. https://doi.org/10.1111/rssa.12125
Wooldridge J (2002) Econometric analysis of cross section and panel data. MIT Press
Acknowledgment
Matthias Studer gratefully acknowledges the support of the Swiss National Science Foundation (project “Strengthening Sequence Analysis,” grant number: 10001A_204740).
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Studer, M., Cianferoni, N. (2023). Sequence Analysis and Its Potential for Occupational Health Studies. In: Wahrendorf, M., Chandola, T., Descatha, A. (eds) Handbook of Life Course Occupational Health. Handbook Series in Occupational Health Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-30492-7_18
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