GESIS Training Courses

Scientific Coordination

André Ernst

Administrative Coordination

Claudia O'Donovan-Bellante
Tel: +49 621 1246-221

Sequence Analysis in the Social Sciences

Online via Zoom
General Topics:
Course Level:
Software used:
Students: 300 €
Academics: 450 €
Commercial: 900 €
Additional links
Lecturer(s): Prof. Dr. Emanuela Struffolino, Prof. Dr. Marcel Raab

About the lecturer - Prof. Dr. Emanuela Struffolino

About the lecturer - Prof. Dr. Marcel Raab

Course description

This workshop introduces sequence analysis for social science research. Sequence analysis, originally developed in biology to analyze strings of DNA, has attracted increasing attention in the social sciences for the analysis of longitudinal data. Most applications study life course processes, including labor market careers, transitions to adulthood, or family formation. This workshop covers longitudinal data management (only briefly), basic techniques of sequence analysis, as well as recent methodological developments tailored at social science research questions. Topics include different ways of calculating distances between sequences, cluster analysis after sequence analysis, sequences visualization, techniques for analyzing sequences' multidimensionality and the association between sequences' unfolding over time and independent variables. All methods are demonstrated with hands-on examples using and R.

Target group

Everyone who is interested in the description and analysis of life courses and longitudinal processes in general (e.g., with time-use data, employment trajectories…).

Learning objectives

The participants will learn
  • how to describe and visualize sequences with the powerful and flexible TraMineR package in R
  • how to use the outcomes from sequence analysis (distance matrices, measures of turbulence and complexity) in further analysis (cluster analysis; regression analysis; discrepancy analysis; implicative statistic for sequences of typical states; sequence analysis multistate model procedure)
  • In short, the participants will learn all the tools required to conduct and publish their own research applying sequence analysis.


    Participants are expected to have some basic knowledge in handling (longitudinal) data and to be familiar with basic quantitative methods (e.g., regression analysis); basic knowledge of R would be beneficial but is not required


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