Gesis Summer School 2024
Survey Methodology
24 July-16 August, 2024, onsite in Cologne
Since 2012, we have been organizing Europe's leading Summer School covering survey methodology, research design, and data collection and analysis. Initially held exclusively at GESIS in Cologne, Germany, we expanded to online options in 2020. This setup brings together lecturers and participants from all over the world and many different fields, fostering a collaborative, global learning environment.
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Week 0
Week 0 (24-26 July)
Short Course A: Introduction to R for Data Analysis (Onsite) (131 kB)
Lecturers: Jan Schwalbach, Dennis Abel
Lecturers: Dorothée Behr, Cornelia Neuert, Lydia Repke
Short Course C: Introduction to Stata for Data Management and Analysis (Online) (214 kB)
Lecturers: Mazlum Karataş, Lynn-Malou Lutz
Week 1
Week 1 (29 July-02 August)
Short Course D: Causal Inference with Directed Acyclic Graphs (DAGs) (Online) (148 kB)
Lecturers: Paul Hünermund
Course 1: Factorial Survey Design (Onsite) (186 kB)
Lecturers: Katrin Auspurg, Carsten Sauer, Alisia Bauer
Course 2: Introduction to Questionnaire Design (Onsite) (381 kB)
Lecturers: Marek Fuchs
Course 3: Designing and Implementing Web Surveys (Onsite) (163 kB)
Lecturers: Melanie Revilla
Week 2
Week 2 (05-09 August)
Short Course E: Mixed-Mode Surveys (Online) (106 kB)
Lecturers: Henning Silber, Sven Stadtmüller, Peter Schmidt, Yannick Diehl
Course 4: Causal Inference Using Survey Data (Onsite) (192 kB)
Lecturers: Heinz Leitgöb, Tobias Wolbring
Course 5: Survey Sampling and Weighting (Onsite) (126 kB)
Lecturers: Simon Kühne
Course 6: Designing, Implementing, and Analyzing Longitudinal Surveys (Onsite) (187 kB)
Lecturers: Tarek Al Baghal, Alexandru Cernat
Week 3
Week 3 (12-16 August)
Course 7: Introduction to Survey Design (Onsite) (177 kB)
Lecturers: Bella Struminskaya, Peter Lugtig
Course 8: Data Science Techniques for Survey Researchers (Onsite) (182 kB)
Lecturers: Anna-Carolina Haensch
Course 9: Introduction to Small Area Estimation (Onsite) (220 kB)
Lecturers: Angelo Moretti
Course 10: Applied Multiple Imputation (Online) (219 kB)
Lecturers: Ferdinand Geißler, Jan Paul Heisig