GESIS Training News

The 7th GESIS Summer School in Survey Methodology will take place from 02 to 24 August 2018 in Cologne. Few places are still available. Don’t miss out on the opportunity to participate in Europe's leading Summer School in Survey Methodology.

Our Short Courses provide excellent and efficient introductions. Here is an overview of the courses with some free places:

Week 0 (02 - 03 August):

Pretesting Survey Questions

Dr. Katharina Meitinger, Dr. Timo Lenzner (GESIS, Germany)

Introduction to Data Analysis Using Mplus

Dr. Matthias Blümke, Dr. Daniel Danner, Dr. Clemens Lechner (GESIS, Germany)

Research Designs and Causal Inference

Prof. Dr. Stefanie Eifler, Dr. Heinz Leitgöb (Catholic University of Eichstätt-Ingolstadt, Germany)

Introduction to Data Analysis Using Stata

Dr. Reinhard Schunck (GESIS, Germany)

Week 3 (20 - 21 August):

Open Science and Open Data

Dr. Sebastian Netscher, Dr. Anja Perry (GESIS, Germany)

Some of our highlights – one-week courses with some free places:

Week 1 (06 - 10 August):

Applied Multiple Imputation

Dr. Ferdinand Geißler (Humboldt-University Berlin, Germany), Dr. Jan Paul Heisig (WZB Berlin, Germany)

The course will introduce you to the concepts of missing data and ways how to overcome some of the issues that arise in analyses with item nonresponse. This class focuses on multiple imputation–the gold standard for dealing with and reducing bias due to missing data in quantitative work.

Week 2 (13 - 17 August):

Mixed-Mode and Mixed-Device Surveys

Prof. Dr. Vera Toepoel, Prof. Dr. Edith de Leeuw (University of Utrecht, The Netherlands), Dr. Thomas Klausch (VU University Medical Center Amsterdam, The Netherlands)

Edith de Leeuw–winner of the WAPOR Helen Dinerman prize for lifetime contributions to the field of public opinion and the ESRA Outstanding Service award–,Vera Toepoel, and Thomas Klausch offer a sound background in Mixed-Mode and Mixed-Device Surveys. The course will address major variants of mixed-mode data collection designs and issues in mixed-mode and mixed-device projects, and show you methods for estimating and adjusting measurement and selection effects. Short lectures will be combined with activities and possible applications to your own research examples or projects.

Web Survey Design

Prof. Mick P. Couper, PhD (University of Michigan, USA), Dr. Ines Schaurer (GESIS, Germany)

Mick P. Couper–author of Designing Effective Web Surveys (Cambridge University Press) and co-editor of The Science of Web Surveys (Oxford University Press)– and Ines Schaurer offer a course on Web Survey Design. You will learn about the effects of design on measurement error and get to know the best possible survey instruments for online data collection. Participants are encouraged to bring their own Web survey projects to class. The instructors will be using the open source software LimeSurvey to demonstrate various design issues.

Evening talks, ECTS Credits & More

We are happy to announce our evening talks on Thursdays:

09.08.: Jan Paul Heisig | "Current Issues in the Identification of Context Effects with Multilevel Data"

16.08.: Panel-Discussion with Edith de Leeuw, Mick Couper, Marek Fuchs | "Present and Future Challenges in Survey Data Collection"

23.08.: Stephanie Eckman | "Can Passive Data Replace Active Data in Surveys?"

Thanks to our cooperation with the Center for Doctoral Studies in Social and Behavioral Sciences, University of Mannheim, participants can obtain up to 4 ECTS points per one-week course. In addition to the courses, participants are welcome to attend evening talks by experts in survey methodology and, thanks to our sponsors, can take part in an exciting social and cultural program.

Register now! You will find more information here!

Also check out our Summer School leaflet!

If you want to know how the Summer School feels like, watch our video.

The GESIS Methodenseminar is aimed at graduate students in the social sciences and humanities as well as related fields. It consists of five courses, three in German, two in English – all are research based and teach practically relevant skills. The Basismodul, Aufbaumodul I, and Aufbaumodul II are held in German and teach basic knowledge and skills on how to analyze quantitative data. The Big Data Modules I and II are held in English and convey knowledge and skills from data science – for example, how to handle and analyze large amounts of data from the internet.

Free spots in the following courses:

Week 1 (09 - 13 July):

Basismodul – Uni- und bivariate Statistik (in German)

Katja Salomo (Friedrich-Schiller University Jena), Dr. Lars Vogel (University of Leipzig)

Week 2 (16 - 20 July):

Aufbaumodul I – Faktorenanalyse und Clusteranalyse mit Stata (in German)

Dr. Stefan Jahr (University of Manchester), Katja Salomo (Friedrich-Schiller University Jena)

Week 3 (23 - 27 July):

Aufbaumodul II – Multiple Regression mit Stata (in German)

Prof. Dr. Michael Gebel, Jonas Voßemer (University of Bamberg)

Thanks to our cooperation with the a.r.t.e.s. Graduate School for the Humanities at the University of Cologne participants of the Methodenseminar may earn 2 European Credit Transfer System (ECTS) points per course for active participation.

Register now! You will find more information here!

Microdata from Eurostat are the basis for comparative social research in Europe. More and more researchers use these data for a wide range of economic and social analyses. Topics addressed in the 6th User Conference include e.g. poverty and social exclusion, income inequality, low wage earners, gender earnings gap, migration and labour mobility, the impact of the financial crisis around 2008 on employment and unemployment, quality of work, innovativeness of enterprises, adult education, skills and qualification, and social aspects of health. In addition to substantive issues, presentations focusing on methodological topics are highly welcome. They may include e.g. questions of data quality, cross-national and inter-temporal comparability as well as the comparability of different EU surveys.

The 6th European User Conference for Eurostat microdata is organized by the German Microdata Lab, GESIS, in cooperation with Eurostat. The conference will provide researchers with the opportunity to present and discuss their latest work and share their experience. In addition to fostering the discussion within the research community on both substantive and methodological issues, the conference offers researchers the opportunity to get into contact with colleagues from Eurostat. Researchers of all disciplines (e.g. economics, sociology, demography, geography, political science and public health) who use Eurostat microdata are encouraged to submit an abstract. All presentations must be comparative and include data from at least two countries. The deadline for submissions of abstracts is 29 September 2018.

For more information, please visit the conference website!

Together with Dr. Ferdinand Geißler (Humboldt-University Berlin, Germany), he will conduct the course “Applied Multiple Imputation” at the 7th GESIS Summer School in August.

How did you become interested in your subject?

I do research on social inequalities and intergenerational mobility. I think that social inequalities in education, health, and income are important and challenging in their own right, yet they also are a likely cause of other social problems such as rising political extremism. Much of my work is comparative. I think that it is really crucial to understand how national institutions shape the magnitude of social inequalities and the chances for upward social mobility, especially for disadvantaged children. My recent methodological work is closely related to my substantive interests and focuses on the identification of context effects with multilevel data such as cross-national surveys.

What lessons can participants draw from your GESIS course?

Participants will learn about the challenges posed by missing data, especially item non-response. Item non-response arises when a survey participant refuses to answer a question or when some pieces of information are missing for other reasons such as coding errors. They will learn why the default approach—using only cases with complete information–is wasteful and can even produce misleading results. The main goal is to introduce participants to multiple imputation as a state-of-the-art technique for addressing these problems. Missing data are a crucial challenge encountered in almost every empirical project, but the problem does not receive much attention in most social science programs. That’s why the course will be a great complement to the training that most people receive in their main programs of study.

What do you enjoy most about being a social scientist?

What I really like about being a social scientist is the opportunity to study interesting questions in a thorough and rigorous way, while at the same time tackling issues of immediate societal relevance. I think that these are exciting times for being a social scientist. I already mentioned the challenge of growing social inequalities. Increasing international migration, growing populism, digitalization, and global warming are other major trends that call for thorough and careful analysis. At the same time, the way we do social science is changing rapidly. The “big data revolution” and other developments–for example, our improving grasp of gene-environment interactions–are opening up exciting new possibilities for understanding social phenomena.

We thank Dr. Heisig for his interesting insights.