GESIS Training Courses

Wiss. Koordination

André Ernst
Tel: +49 221 4703736

Administrative Koordination

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
Dozent(en): Dr. Marcel Raab, Emanuela Struffolino

Referenteninformationen - Dr. Marcel Raab

Referenteninformationen - Emanuela Struffolino


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 to analyze longitudinal data. Most applications in the social sciences 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 to social science research questions. Topics include different ways of calculating distances between sequences, cluster analysis after sequence analysis, sequence 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 R.


Participants will find the course useful if:
  • they work with longitudinal categorical data
  • they are interested in describing temporal patterns of social phenomena

  • Lernziel

    By the end of the course participants will:
  • be able to conduct their own research by applying sequence analysis
  • know how to describe and visualize sequences with the powerful and flexible TraMineR package in R
  • know how to use the outcomes from sequence analysis (distance matrices, measures of turbulence and complexity) in further analyses (cluster analysis; regression analysis; discrepancy analysis; implicative statistic for sequences of typical states; sequence analysis multistate model procedure)
    Organizational structure of the course
    The course is structured around sessions of instructions and hands-on exercises. The hands-on sessions consist of assignments that aim at consolidating the content of the instruction session by applying them in R. During the hands-on sessions, the lecturers are available to address problems that might arise and answer questions, and they will discuss the solutions before moving to the next instructions session. If needed, separate virtual rooms will be used for 1:1 tutoring. During the instruction sessions, one of the lecturers is available in the chat. Further, lecturers will be available for individual consultations on participants' projects.


  • basic knowledge in handling (longitudinal) data
  • basic knowledge of quantitative methods (e.g., regression analysis)
  • basic knowledge of R is strongly recommended (e.g., inspecting, visualizing, transforming your data, extracting values from a table, sub-setting tables, calculating summary statistics, and deriving new variables). For an introduction to the basics, you might consider consulting datacamp or the following primers by posit cloud (formerly RStudio Cloud): primer 1, primer 2, and primer 4.
    Software requirements
    The latest version of R and RStudio should be installed on participants' laptops. Shortly before the course, the lecturers will circulate further instructions.