GESIS Training News

The GESIS Training Team is very concerned about the health of participants and lecturers of our courses. However, we know many of you (just like us) love to meet in person again. Thus we are happy to offer in-person courses. Please respect that local restrictions may apply due to the coronavirus. Because we know that some of you prefer online classes altogether, digital courses are now part of our regular program. More information here.

Stay well and safe!

The Spring Seminar offers high-quality training in state-of-the-art techniques in quantitative data analysis taught by leading experts in the field. It is designed for advanced graduate or PhD students, post-docs, as well as junior and senior researchers. In 2023, all courses will deal with techniques and methods for "Modeling Group Differences" in the social sciences and beyond. Extensive hands-on exercises and tutorials complement lectures in each course. All courses are held in English. The Spring Seminar will take place on-site in Cologne, Germany, from 27 February to 17 March 2023. Only if the pandemic hits again heavily will we move the courses online.

Week 1 (27 Feb-03 Mar)

Comparative Social Research with Multi-Group SEM

Daniel Seddig, Eldad Davidov, Peter Schmidt, Yannick Diehl   

Week 2 (06-10 Mar)

Decomposition Methods in the Social Sciences

Johannes Giesecke, Ben Jann   

Week 3 (13-17 Mar)

Latent Class Analysis

Daniel Oberski   

There is no registration deadline, but places are limited and allocated on a first-come, first-served basis. Our cooperation with the Cologne Graduate School in Management, Economics and Social Sciences at the University of Cologne allows enrolled doctoral students to obtain three ECTS credit points per one-week course.

For registration and detailed course descriptions, please visit our website!

The year is drawing to a close. Therefore we have a special end of year gift for you. A workshop free of charge!

While more and more users turn their back on Twitter and join Mastodon, David Schoch (GESIS) and Chung-hong Chan (GESIS) have implemented the R-package rtoot (#rstats), to connect with the Mastodon API. David will present the package in a free-of-charge online mini workshop hosted by GESIS Training on 16 December, 2022 from 12 pm to 1.30 pm.

Keep right up to date, and register for our workshop "rtoot: Interacting with the Mastodon API from R".

This year is quickly coming to an end - and 2023 is just around the corner! We still have a couple of exciting workshops, e.g. on causal mediation analysis or using social media data for research, lined up for December before we kick off 2023 with workshops on e.g. multiverse analysis, DAGs or programming web surveys.

In addition to these workshops, the first half of 2023 will feature workshops on collecting data from the Twitter API (late March), sensor data for social science research (mid-April), data viz with R (May), and linking Twitter and survey data (mid-June). We'll update our website regularly, so stay tuned!

You can find the full list of confirmed workshops below.

A successful tradition has been continued for the eleventh time. Europe’s leading summer school in survey methodology took place for the first time in a hybrid format from 03 to 26 August 2022. Over 200 participants from the international academic community took part in a series of excellent virtual and on-site courses on methods and techniques of survey methodology. Fourteen courses were scheduled, including four short courses and ten one-week courses. Six courses were held on-site in Cologne, and the other eight were delivered via Zoom. The program combined introductory and advanced courses, aiming to suit the preferences and needs of a broader academic audience. Keeping pace with the new trends in survey methodology, three courses were new or wholly redesigned: “Data Science Techniques for Survey Researchers”, “Sampling and Weighting in Survey Statistics”, and “Mixed-Mode Surveys”. Participants evaluated the courses... [Continue reading]

If you could not make it this summer, please save the date for next year's event – 02 to 25 August 2023 – on-site at GESIS Cologne and online via Zoom.

For more information on the Summer School, visit www.gesis.org/summerschool.

Stay tuned!

Following the successful launch of the Fall Seminar in Computational Social Science in 2021, 2022 saw us expanding the Fall Seminar program to a total of nine one-week courses on computational social science methods and techniques. From 05 to 23 September 2022, participants could choose from a variety of introductory and advanced courses on the foundations of working with digital behavioral data, data collection and management, and data analysis. [Continue reading]

Save the date: The Fall Seminar 2023 will take place from 11 to 29 September 2023 at GESIS Mannheim. We will announce the full program in Spring 2023.

For more information on the Fall Seminar, visit www.gesis.org/fallseminar.

Johannes is professor of sociology at the Humboldt University of Berlin. His research interests include labor market sociology, social inequality, and quantitative methods. He is head of the department “Labor Market, Migration, and Integration” at the Berlin Institute for Empirical Integration and Migration Research (BIM) and research fellow at the German Institute for Economic Research (DIW). Ben is professor of sociology at the University of Bern. His research interests include social science methodology, statistics, social stratification, and labor market sociology. He is principal investigator of TREE, a large-scale multi-cohort panel study in Switzerland on transitions from education to employment (www.tree.unibe.ch). He is the author of many Stata packages, among them a widely used package for Oaxaca-Blinder decompositions (Jann 2008). They will teach the course “Decomposition Methods in the Social Sciences” at the GESIS Spring Seminar 2023.

How did you become interested in your subject?

Johannes: I started looking into decomposition methods more closely in the mid-2000s. At that time, I was interested in analyzing the factors that lay behind the relatively strong increase in wage inequality in Germany since the mid-1990s.

Ben: I started using decomposition techniques early in my academic career, mostly for analyses of the development of the gender wage gap in Switzerland. In addition to the applied topic, I was also interested in the methodological aspects of the techniques. For example, I wrote a highly cited paper on statistical inference for the Oaxaca-Blinder decomposition and made various software packages available that implement different variants of decomposition techniques.

What lessons can participants draw from your GESIS course?

Johannes & Ben: Participants will learn that while the basic idea of decomposing outcome gaps between groups is straightforward, things are more challenging regarding a real-world problem. However, participants will be well-equipped to face this challenge.

What do you enjoy most about being a social scientist?

Johannes: To do research that has societal relevance. And to have the academic freedom to choose my research topics myself.

Ben: This is a difficult question because there are so many things I like about my job, and I find it hard to decide what I like most. One aspect I particularly enjoy is that I have the freedom to delve into a topic and take the time I need to think it through.

We thank Johannes & Ben for their interesting insights and look forward to their class.