Limited seats available, should you be interested in attending this course, please email us at: firstname.lastname@example.org and we will get back to you and confirm availability.
Trainer: Matthias Studer
Associate Professor, LIVES Centre and Institute of Demographics and Socioeconomics, University of Geneva.
Trainer Assistance: Bozena Wielgoszewska
Research Associate at Centre for Longitudinal Studies, UCL
The methodological workshop provides a two-day course on sequence analysis, a methodological framework to study trajectories described as a sequence of categorical states, such as familial or professional trajectories. The workshop is aimed to a large audience, starting with a general overview on the uses of sequence analysis in the social sciences and how to define trajectories in a life course perspective. It then presents descriptive and visualization methods, before moving to the creation of a typology of trajectories focusing on the different choices to be made (cluster algorithms, distance measures, cluster quality measures). The course also discusses data management for sequence analysis, missing data handling and multichannel sequence analysis. Each theoretical presentation is followed by practical sessions on how to run all the presented analysis using R, TraMineR and WeightedCluster. The workshop also includes a short introduction to R for those not familiar with the software.
Prior knowledge of a statistical software (not necessarily R). (Understanding of regression models is recommended.
|Wed. October 13||Thurs. October 14|
|09.00 – 10:15||General Introduction to sequence analysis and short introduction to R||09.00 – 10:15||Optimal matching, other distance measures, and multichannel sequence analysis|
|10.15 – 10.45||Break||10.15 – 10.45||Break|
|10.45 – 12.00||Descriptive sequence analysis and visualization I||10.45 – 12.00||Advanced clustering technic|
|12.00 – 13.15||Lunch||12.00 – 13.15||Lunch|
|13.15 – 14.30||Descriptive sequence analysis and visualization II||13.15 – 14.30||Discrepancy analysis and multidimensional scaling|
|14.30 – 15.00||Break||14.30 – 15.00||Break|
|15.00 – 16.15||Clustering states sequences using Hamming distances||15.00 – 16.15||Missing data & longitudinal data management|