With Marcel Raab (University of Mannheim).
In preparation for the SAGE’s Quantitative Applications in the Social Sciences (QASS)
How does the school-to-work transition process look like in different countries? Do individual electoral participation pattern differ across context with varying degrees of residential segregation? How similar are employment biographies across cohorts of workers who entered the labor market before and after the recent economic crisis? Do democratization processes differ depending on the pathways of turnover between rightist and leftist parties? Answering these research questions requires the application of analysis tools that capture how processes unfold over time. Within the toolkit of longitudinal methods, we consider social sequence analysis to be one of the most powerful and versatile ones – particularly when it comes to studying longitudinal categorical data.
Sequence analysis was introduced in the social sciences in the 1980s. Andrew Abbott, inspired by the treatment of DNA strings in biology, developed it as a technique to study social processes that unfold over time as sequences of events (Abbott & Forrest, 1986). Sequence analysis has gained increasing attention as the recent widespread availability of longitudinal data made it possible to address sequence-oriented questions. The mainstream application of sequence analysis relies on optimal matching techniques to measure the distance between sequences that represent the individual realization of a certain process and on the clustering of such sequences to identify typical trajectories. Regression analysis is often applied as a second step to investigate why (and not only how) sequences resemble or differ from each other. In the last ten years, several innovations have been introduced to overcome weaknesses and limitation of the initial proposition. A sequence analysis introductory book is currently missing in the QASS series. Therefore, the book will complement the rich catalogue of the QASS series with an up-to-date introduction to a technique that is steadily gaining popularity.
Several statistical software tools made it available to a broader public. However, existing publications on sequence analysis that might serve the purpose of teaching and learning its basics, are scattered across several journal articles, books, and software documentations. This makes it hard for newcomers to figure out where to start and to identify good practices for performing methodologically sound analyses. To answer these needs, the book introduces the basics of sequence analysis to guide practitioners and support instructors along the working flow of sequence analysis. The presentation of statistical, substantive, and theoretical foundations will be enriched by examples to help the reader in understanding the advantages and disadvantages of specific analytical choices. The extensive ancillary material will support self-learning by offering exercises and solutions based on real data and research questions in the field of life course research. Finally, the book will include practical guidelines considering recent advances and innovations in sequence analysis.