Spring Seminar | Methodenseminar | Summer School | Workshops

This year, the Spring Seminar took place for the 47th time at GESIS Cologne. It started on February 19th with a course on "Multilevel Analysis" held by Prof. Ian Brunton-Smith and Nigel de Noronha. In the second week our participants learned how to analyze spatially dependent data in the course "Spatial Analysis and Spatial Econometrics" by Prof. Jude C. Hays and Ass. Prof. Scott J. Cook. The Spring Seminar ended with a course on "Longitudinal Network Analysis Using RSiena" offered by Prof. Tom A.B. Snijders und Dr. András Vörös. [Continue reading on facebook.]

The 7th GESIS Summer School in Survey Methodology will take place from 02 to 24 August 2018 in Cologne. 15 courses are scheduled, among them 5 short courses and 10 one-week courses. New to the program are courses on "Pretesting Survey Questions", "Applied Multiple Imputation", and "Open Science and Open Data". The courses "Mixed-Mode and Mixed-Device Surveys" and "Web Survey Design" are back in our program. Don't miss out on the opportunity to participate in Europe's leading Summer School in Survey Methodology.

Here is an overview of this year's courses:

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 1 (06 - 10 August):

Introduction to Survey Design

Prof. Dr. Peter Lugtig, Prof. Dr. Bella Struminskaya (University of Utrecht, The Netherlands)

Introduction to Structural Equation Modeling: Confirmatory Factor Analysis with Mplus

Prof. Dr. Jost Reinecke, Georg Kessler (University of Bielefeld, Germany)

Introduction to Data Analysis Using R

Dr. Jan-Philipp Kolb, Alexander Murray-Watters (GESIS, Germany)

Applied Multiple Imputation

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

Week 2 (13 - 17 August):

Questionnaire Design

Prof. Dr. Marek Fuchs, Anke Metzler (Darmstadt University of Technology, Germany)

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)

Web Survey Design

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

Week 3 (20 - 24 August):

Meta-Analysis in Social Research and Survey Methodology

Dr. Bernd Weiß, Jessica Daikeler (GESIS, Germany)

Sampling, Weighting, and Estimation

Stephanie Eckman, PhD (RTI International, USA)

Designing, Implementing, and Analyzing Longitudinal Surveys

Dr. Tarek Al Baghal (University of Essex, United Kingdom), Dr. Alexandru Cernat (University of Manchester, United Kingdom)

Open Science and Open Data

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

ECTS Credits & More

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.

The Methodenseminar 2018 consists of 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)

Big Data Module I - Introduction to Data Science with Python (in English)

Dr. Arnim Bleier, Dr. Fabian Flöck, Dr. Florian Lemmerich, Dr. Haiko Lietz (GESIS Cologne)

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)

Big Data Module II - Text Mining with R (in English)

Dr. Andreas Niekler (University of Leipzig), Dr. Gregor Wiedemann (University of Hamburg)

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!

The 9th User Conference "Forschen mit dem Mikrozensus" (conference language: German) will take place in Mannheim on 27-28 November 2018. The Conference focuses on social structure and social change in Germany. It brings data producers and data users together to exchange experiences and to discuss recent research carried out based on the German Microcensus data. The conference is organized by the German Microdata Lab (GML) of GESIS and by the Federal Statistical Office (Destatis - Division H 3: Household Surveys, Housing) in cooperation with the Research Data Centres of the Federal Statistical Office and the statistical offices of the Länder.

Proposals can be submitted until June 30, 2018. For more information, please visit the conference website!

Together with Dr. Arnim Bleier, Dr. Fabian Flöck (both GESIS-CSS), and Dr. Florian Lemmerich (RWTH Aachen), he will conduct the course "Introduction to Data Science with Python" at the 38th GESIS Methodenseminar in July.

How did you become interested in your subject?

I've always been interested in the substance of things - how things work -, looking behind the way they present themselves. As a journalist, the way to do this was Computer-Assisted Reporting. In that time, I first encountered Social Network Analysis, the prime method to study mechanisms. A Fulbright scholarship then allowed me to become a student of Harrison C. White in the US and specialize in network analysis and theory. There is no typical way into Data Science, and neither is mine.

What lessons can participants draw from your GESIS course?

Data Science is not rocket science. A programing language like Python can be learned by doing it. This can be quite mundane. If one encounters a problem, a search engine will typically find the answer. If not, fellow users on the question-and-answer site stackoverflow.com will have an answer, typically within the same day. This is how I - and many of us who are not computer scientists - have learned how to program. Participants will also see that, and how, the data-driven approach is very untypical for the social sciences which often depart from theory.

What do you enjoy most about being a social scientist?

We live at a unique point in time. What kind of global civilization we will soon be depends on how we handle inequality, climate change, mass surveillance, or Artificial Intelligence now. As a sociologist, I try to contribute to understanding social systems as constantly changing processes. We finally have the data to do so. We should use it for creating a better, fairer, and more just future.

We thank Dr. Lietz for his interesting insights.

Copyright © 2018 GESIS. All rights reserved.

subscribe or unsubscribe from this list.

Spring Seminar | Methodenseminar | Summer School | Workshops

This year, the Spring Seminar took place for the 47th time at GESIS Cologne. It started on February 19th with a course on "Multilevel Analysis" held by Prof. Ian Brunton-Smith and Nigel de Noronha. In the second week our participants learned how to analyze spatially dependent data in the course "Spatial Analysis and Spatial Econometrics" by Prof. Jude C. Hays and Ass. Prof. Scott J. Cook. The Spring Seminar ended with a course on "Longitudinal Network Analysis Using RSiena" offered by Prof. Tom A.B. Snijders und Dr. András Vörös. [Continue reading on facebook.]

The 7th GESIS Summer School in Survey Methodology will take place from 02 to 24 August 2018 in Cologne. 15 courses are scheduled, among them 5 short courses and 10 one-week courses. New to the program are courses on "Pretesting Survey Questions", "Applied Multiple Imputation", and "Open Science and Open Data". The courses "Mixed-Mode and Mixed-Device Surveys" and "Web Survey Design" are back in our program. Don't miss out on the opportunity to participate in Europe's leading Summer School in Survey Methodology.

Here is an overview of this year's courses:

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 1 (06 - 10 August):

Introduction to Survey Design

Prof. Dr. Peter Lugtig, Prof. Dr. Bella Struminskaya (University of Utrecht, The Netherlands)

Introduction to Structural Equation Modeling: Confirmatory Factor Analysis with Mplus

Prof. Dr. Jost Reinecke, Georg Kessler (University of Bielefeld, Germany)

Introduction to Data Analysis Using R

Dr. Jan-Philipp Kolb, Alexander Murray-Watters (GESIS, Germany)

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

Week 2 (13 - 17 August):

Questionnaire Design

Prof. Dr. Marek Fuchs, Anke Metzler (Darmstadt University of Technology, Germany)

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)

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

Week 3 (20 - 24 August):

Meta-Analysis in Social Research and Survey Methodology

Dr. Bernd Weiß, Jessica Daikeler (GESIS, Germany)

Sampling, Weighting, and Estimation

Stephanie Eckman, PhD (RTI International, USA)

Designing, Implementing, and Analyzing Longitudinal Surveys

Dr. Tarek Al Baghal (University of Essex, United Kingdom), Dr. Alexandru Cernat (University of Manchester, United Kingdom)

Open Science and Open Data
Dr. Sebastian Netscher, Dr. Anja Perry (GESIS, Germany)

ECTS Credits & More

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.

The Methodenseminar 2018 consists of 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)

Big Data Module I - Introduction to Data Science with Python (in English)

Dr. Arnim Bleier, Dr. Fabian Flöck, Dr. Florian Lemmerich, Dr. Haiko Lietz (GESIS Cologne)

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)

Big Data Module II - Text Mining with R (in English)

Dr. Andreas Niekler (University of Leipzig), Dr. Gregor Wiedemann (University of Hamburg)

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!

The 9th User Conference "Forschen mit dem Mikrozensus" (conference language: German) will take place in Mannheim on 27-28 November 2018. The Conference focuses on social structure and social change in Germany. It brings data producers and data users together to exchange experiences and to discuss recent research carried out based on the German Microcensus data. The conference is organized by the German Microdata Lab (GML) of GESIS and by the Federal Statistical Office (Destatis - Division H 3: Household Surveys, Housing) in cooperation with the Research Data Centres of the Federal Statistical Office and the statistical offices of the Länder.

Proposals can be submitted until June 30, 2018. For more information, please visit the conference website!

Together with Dr. Arnim Bleier, Dr. Fabian Flöck (both GESIS-CSS), and Dr. Florian Lemmerich (RWTH Aachen), he will conduct the course "Introduction to Data Science with Python" at the 38th GESIS Methodenseminar in July.

How did you become interested in your subject?

I've always been interested in the substance of things - how things work -, looking behind the way they present themselves. As a journalist, the way to do this was Computer-Assisted Reporting. In that time, I first encountered Social Network Analysis, the prime method to study mechanisms. A Fulbright scholarship then allowed me to become a student of Harrison C. White in the US and specialize in network analysis and theory. There is no typical way into Data Science, and neither is mine.

What lessons can participants draw from your GESIS course?

Data Science is not rocket science. A programing language like Python can be learned by doing it. This can be quite mundane. If one encounters a problem, a search engine will typically find the answer. If not, fellow users on the question-and-answer site stackoverflow.com will have an answer, typically within the same day. This is how I - and many of us who are not computer scientists - have learned how to program. Participants will also see that, and how, the data-driven approach is very untypical for the social sciences which often depart from theory.

What do you enjoy most about being a social scientist?

We live at a unique point in time. What kind of global civilization we will soon be depends on how we handle inequality, climate change, mass surveillance, or Artificial Intelligence now. As a sociologist, I try to contribute to understanding social systems as constantly changing processes. We finally have the data to do so. We should use it for creating a better, fairer, and more just future.

We thank Dr. Lietz for his interesting insights.

Copyright © 2018 GESIS. All rights reserved.

subscribe or unsubscribe from this list.