Abstract
This chapter is an entry-level introduction to sequence analysis, which is a set of techniques for exploring sequential quantitative data such as those contained in life histories. We illustrate the benefits of the approach, discuss its links with the life course perspective, and underline its importance for studying personal histories and trajectories, instead of single events. We explain what sequential data are and define the core concepts used to describe sequences. We give an overview of tools that sequence analysis offers, distinguishing between visually descriptive, numerically descriptive, and more analytical techniques, and illustrate concepts with examples using life history data. Graphical methods such as index plots, chronograms, and modal plots give us an intuitive overview of sequences. Numerically descriptive tools including the cumulative duration, number and duration of spells, as well as sequence complexity give a more statistical and quantitative grasp on the key differences between sequences. Comparing how similar sequences are, by calculating distances, either between sequences or to an ideal type, allows grouping sequences for more analytical research purposes. We conclude with a discussion on the possibilities in terms of hypothesis testing of this mainly explorative analytical technique.
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Vanhoutte, B., Wahrendorf, M., Prattley, J. (2018). Sequence Analysis of Life History Data. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences . Springer, Singapore. https://doi.org/10.1007/978-981-10-2779-6_146-1
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