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This chapter proposes a novel sequential mixed-method design that brings together the strengths of sequence analysis (SA) and qualitative comparative analysis (QCA). Both methods rely on an epistemological framework that combines analytical and holistic elements: they share the notion of analytically approaching social phenomena without disregarding their complexity. We apply SA as a first step to analyze the unfolding of phenomena over time. Specifically, through discrepancy analysis of state sequences, one can identify the time points when trajectories (start to) diverge from each other. In a second, explanatory step, QCA is applied to investigate whether, at such crucial time points, some particular configurations of factors are logically sufficient for the occurrence of a given state (or outcome). We provide an illustrative application to women's employment trajectories in divided Germany by using data from the Adults Cohort of the German National Educational Panel (NEPS). By preserving the analytical and holistic perspective on trajectories, our proposed design highlights the dynamic of socio-demographic factors sufficient for women to be in employment or education at critical turning points over the life course. This design takes on the challenge, summarized in Abbott's call for a 'processual sociology', to investigate both the dynamics of social phenomena as lineages of successive events and the complexity of contextual characteristics of 'present' moments. We conclude with an overview of research fields where our framework holds the promise of being applied fruitfully, namely life-course research, social stratification studies, policy evaluation, and comparative politics.

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. ; Provides new perspectives and methods for sequence analysis Focusses on the link between sequence analysis and other methods for longitudinal data, especially event history analysis and Markov models Stresses the complementarity of sequence analysis and other models for longitudinal data Applications of sequence analysis in a whole range of different domains