Sequence Analysis and Related Approaches, 1st ed. 2018 Innovative Methods and Applications Life Course Research and Social Policies Series, Vol. 10

This open access book provides innovative methods and original applications of sequence analysis (SA) and related methods for analysing longitudinal data describing life trajectories such as professional careers, family paths, the succession of health statuses, or the time use. The applications as well as the methodological contributions proposed in this book pay special attention to the combined use of SA and other methods for longitudinal data such as event history analysis, Markov modelling, and sequence network. The methodological contributions in this book include among others original propositions for measuring the precarity of work trajectories, Markov-based methods for clustering sequences, fuzzy and monothetic clustering of sequences, network-based SA, joint use of SA and hidden Markov models, and of SA and survival models. The applications cover the comparison of gendered occupational trajectories in Germany, the study of the changes in women market participation in Denmark, the study of typical day of dual-earner couples in Italy, of mobility patterns in Togo, of internet addiction in Switzerland, and of the quality of employment career after a first unemployment spell. As such this book provides a wealth of information for social scientists interested in quantitative life course analysis, and all those working in sociology, demography, economics, health, psychology, social policy, and statistics.

Matthias Studer, PhD in socioeconomics, is a Senior Researcher at the Swiss NCCR program ``LIVES overcoming vulnerability: life course perspectives'' and a Lecturer at the Geneva School of Social Sciences of the University of Geneva. His research interests include quantitative methods for longitudinal data analysis, sequence analysis, gendered career inequalities, labor market and social policy evaluation. He is one of the TraMineR developers, and he recently published on Discrepancy Analysis in Sociological Methods \& Research and a comparison of sequence analysis distance measures in the Journal of the Royal Statistical Society: Series A.