Author Archives: sfietze

Questionnaire Design

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Daniel Schnitzlein (Leibniz University Hannover & Inside Statistics)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The course provides an overview of the theoretical basics and empirical evidence related to questionnaire design. The cognitive process of survey responding, challenges of designing effective survey questions including aspects of proper question wording and optimal response formats, as well as pretest techniques for evaluating survey questions will be discussed. The lecture will be accompanied by a practical part.

You have to register for the International Research Workshop to participate in this course.

Academic English Writing

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonathan Mole (Europa-Universität Flensburg)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Writing an academic text is a complex task. It requires knowledge of a range of accepted writing conventions, as well as the ability to construct sentences that are not only idiomatically and grammatically correct but also suitably connected to one another. An awareness of the requirements and a degree of practice are necessary.

This workshop is primarily for people who are in the process of writing an academic text in English – a proposal, abstract, article, thesis etc. It provides the opportunity to obtain individual feedback on a text which you submit prior to the workshop. In the workshop, assistance will be given to enable you to self-correct any issues which have been highlighted (structure, understanding, logic, language etc.). In addition, an overview of the important characteristics of academic English writing will be discussed. If required, exercises will be available to highlight topics such as academic style (formality, impersonal and objective language, passive voice, caution, nominalisation); structure a sentence, paragraph and document level; reporting verbs and their forms; coherence and cohesion; and citation and reference styles.

A requirement of students: Please supply a maximum of 2 pages of text at least two weeks before the workshop begins. English language skills at CEFR level B2/C1 are required.

Recommended literature and pre-reading: None.

You have to register for the International Research Workshop to participate in this course.

Qualitative Comparative Analysis (QCA)

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonas Buche (Leibniz University Hannover)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Since the publication of the seminal work “The Comparative Method” by Charles Ragin in 1987, set-theoretic methods and especially Qualitative Comparative Analysis (QCA) have become a common research strategy in the social sciences. Set-theoretic methods analyse cases with regard to the identification of sufficient and necessary conditions and assume set relations to be equifinal, conjunctural and asymmetric. Not least since so-called fuzzy sets have been introduced to the method, there has been a rising interest in QCA as a welcome alternative to both small-n case studies and large-n statistical analyses. In short, QCA is recommended if ‘if…then’ hypotheses are analysed; if the goal is to derive sufficient and necessary conditions; if a comparison is planned; and if there is a mid-sized number of cases (between 10 and 60+).

The course offers a comprehensive introduction to QCA and is both conceptually and technically oriented. It starts off with an overview of the basics of set theory and demarcates QCA as a case-oriented method from both the quantitative and the interpretive-qualitative research paradigm. Through the notion of necessary and sufficient conditions and of truth tables, the single elements are built into the Truth Table Algorithm. However, this algorithm is not free of problems. Therefore, some pitfalls and strategies on how to overcome them are presented. On the third day, the software tool fsQCA will be introduced and applied to published studies.

A requirement of students: No prior knowledge is required. We will use the software fsQCA2.5 which can be downloaded at www.fsqca.com.

Recommended literature and pre-readings:

You have to register for the International Research Workshop to participate in this course.

CfA: “Causality in the Social Sciences III – Heterogeneous Causal Effects”

The workshop “Causality in the Social Sciences III – Heterogeneous Causal Effects” picks up on recent approaches and debates on causal effect heterogeneity from three different angles:

(i) Interpretation of heterogeneous effects,
(ii) estimating heterogeneous effects with observational and experimental data, and
(iii) machine learning techniques for specification search.

Confirmed keynote speakers are Jennie E. Brand (UCLA), and Richard Breen (Oxford University).

We accept a maximum of 15 presentations. Workshop participation is free of charge. Application deadline: 30 June 2021.

For further information and a detailed call for applications, please visit www.gesis.org/causality-workshop.

2nd Virtual GESIS Summer School in Survey Methodology

The 10th GESIS Summer School — Europe’s leading summer school in survey methodology, research design, and data collection — will take place online as the 2nd Virtual GESIS Summer School from 28 July to 20 August 2021. Scheduled are four short courses and ten one-week courses. You may earn 4 ECTS credits by writing a

For all relevant information including the full program and detailed course descriptions visit www.gesis.org/summerschool.

GESIS Fall Seminar in Computational Social Science 2021

Dear readers of PhD Network,

We are excited to announce the program of the GESIS Fall Seminar in Computational Social Science 2021, held virtually from 13 September to 01 October 2021.

The GESIS Fall Seminar targets social scientists, data scientists, and researchers in the digital humanities that want to collect and analyze data from the web, social media, or digital text archives. Organized along two parallel tracks, it offers six one-week courses on computational social science methods and techniques using either R or Python. Lectures in each course are complemented by hands-on exercises giving participants the opportunity to apply these methods to data. All courses are held in English.

Computational Social Science with R

Introduction to Computational Social Science with Applications in R (13-17 September)
Dr. Aleksandra Urman, University of Bern / University of Zurich (Switzerland)
Max Pellert, Medical University of Vienna / Technical University of Graz (Austria)
Automated Web Data Collection with R (20-24 September)
Dr. Theresa Gessler, University of Zurich (Switzerland)
Hauke Licht, University of Zurich (Switzerland)
Social Network Analysis with R (27 September-1 October)
Dr. Silvia Fierăscu, West University of Timișoara (Romania)
Ianis Rușitoru, West University of Timișoara (Romania)

Computational Social Science with Python

Introduction to Computational Social Science with Python (13-17 September)
Dr. Orsolya Vásárhelyi, University of Warwick (United Kingdom)
Luis Natera, Central European University Budapest (Hungary)
Web Data Collection and Natural Language Processing in Python (20-24 September)
Indira Sen, GESIS (Germany)
Dr. Arnim Bleier, GESIS (Germany)
Julian Kohne, GESIS (Germany)
Dr. Fabian Flöck, GESIS (Germany)

A Practical Introduction to Machine Learning in Python (27 September-1 October)
Assoc. Prof. Damian Trilling, University of Amsterdam (Netherlands)
Assist. Prof. Anne Kroon, University of Amsterdam (Netherlands)

Courses will be held online via Zoom and can be booked either separately or as a block. There is no registration deadline, but places are limited and allocated on a first-come, first-served basis. To secure a place in the course(s) of your choice, we strongly recommend that you register early. Thanks to our cooperation with the a.r.t.e.s. Graduate School for the Humanities at the University of Cologne, participants of the GESIS Fall Seminar can obtain 2 ECTS credit points per one-week course.

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

For further training opportunities, have a look at our Summer School in Survey Methodology and workshop program.

Sign up for our newsletter to never miss any GESIS Training course.

Multi-level Modelling with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Daniel Lüdecke (UKE Hamburg)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The course teaches how to fit multilevel regression models with the statistical programming language R. First, simple (generalized) linear regression models are introduced to show important basic principles of modelling, like simple regression, interaction terms, non-linear relationships between predictors and outcome (polynomial and spline terms). Later, the application of these principles in a multilevel framework is demonstrated. Furthermore, graphical representation of complex mixed models is covered that help communicate complicated models in a simple way even for a broad audience that is less familiar with such modelling techniques. Successful participation requires basic knowledge of regression modelling techniques. Students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed. All source code to run the examples is provided in preparation for the course.

Requirements: Basic knowledge of regression modelling (familiarity with terms like dependent and independent variables, linear and logistic regression, estimate, …)

Recommended readings:

  • Harrison, X. A., Donaldson, L., Correa-Cano, M. E., Evans, J., Fisher, D. N., Goodwin, C. E. D., … Inger, R. (2018). A brief introduction to mixed-effects modelling and multi-model inference in ecology. PeerJ, 6, e4794. https://doi.org/10.7717/peerj.4794
  • Bolker, B. M., Brooks, M. E., Clark, C. J., Geange, S. W., Poulsen, J. R., Stevens, M. H. H., & White, J.-S. S. (2009). Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology & Evolution, 24(3), 127–135. https://doi.org/10.1016/j.tree.2008.10.008

Required R packages:

  • Modelling: lme4, glmmTMB, GLMMadaptive
  • Visualization: ggeffects, sjPlot, see
  • Summaries and Statistics: parameters, effectsize
  • Model Quality: performance
  • Data preparation: sjmisc, dplyr, tidyr

Run install.packages(c(“lme4”, “glmmTMB”, “parameters”, “performance”, “effectsize”, “see”, “GLMMadaptive”, “ggeffects”, “sjPlot”, “sjmisc”, “dplyr”, “tidyr”), dependencies = TRUE) to install the relevant packages.

You have to register for the International Research Workshop to participate in this course.

Data Analysis with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Marco Lehmann (UKE Hamburg)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The course introduces the programming language R used for statistical analyses. The beginning of each lecture comes with a demonstration of programming and statistical functions that will be elaborated on in the course of study. The students will then practice with many statistical examples. In addition to statistical functions, the course will introduce the definition of R as a programming language and its syntax rules. Students will further learn to use R’s scripting capabilities. Successful participation requires basic knowledge of descriptive and inferential statistics. The students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed.

A requirement of students: Basic knowledge in descriptive and inferential statistics is recommended.

Recommended literature and pre-readings:

  • Matloff, N. (2011). The Art of R Programming: A Tour of Statistical Software Design. No Starch Press.
  • Wollschläger, Daniel (2012). Grundlagen der Datenauswertung mit R (2. Aufl.). Berlin: Springer.

You have to register for the International Research Workshop to participate in this course.

Case Study Research

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: PD Dr. Kamil Marcinkiewicz (University of Hamburg)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Case study research is frequently applied in the social sciences. It is particularly popular among political scientists, especially those specialising in area studies. The ubiquity of the case study research contrasts with the scarcity of theoretical reflection on its core methodological aspects. Also, the benefits of comparative analyses are often underestimated. In this course, participants will have an opportunity to learn more about what case study research is, what are its weakness and strengths and how should we go about the core question in designing a case study: a selection of cases. The course combines lectures with practical exercises and discussion of students’ projects.

A requirement of students: Please bring your laptop computer.

Recommended literature and pre-readings:

  • Gerring, J. (2007). Case Study Research: Principles and Practices (pp. 17-63). Cambridge: Cambridge University Press.
  • George, A. L., & Bennett, A. (2005). Case Studies and Theory Development in the Social Sciences (pp. 1-34). Cambridge, MA: MIT Press.
  • Rueschemeyer, D. (2003). Can One or a Few Cases Yield Theoretical Gains? In J. Mahoney and D. Rueschemeyer (Eds.), Comparative Historical Analysis in the Social Sciences (pp. 305-337) Cambridge: Cambridge University Press.
  • Hall, P.A. (2008). Systematic Process Analysis: When and How to Use it. European Political Science, 7(3), 304-317.

You have to register for the International Research Workshop to participate in this course.

Call for Applications for the ARL International Summer School 2021

“Urban and Regional Infrastructures”
WED 29 September – SAT 2 October 2021 in Vienna

The ARL – Academy for Territorial Development in the Leibniz Association in cooperation with the University of Vienna is inviting applications for the ARL International Summer School 2021 on “Urban and Regional Infrastructures”, which will take place from Wed. 29 September to Sat. 2 October, 2021 in Vienna (the arrival is scheduled for 28 September 2021). Advanced master and doctoral students from all disciplines are invited to apply. The summer school will be held in English. The deadline for applications is 11th April 2021.

Please see the call for applications for further information on the event, the terms of participation, and information on the application process:

https://www.arl-net.de/en/projekte/arl-international-summer-school-2021

For further questions, please contact Dr. Lena Greinke (greinke@arl-net.de, +49 (0)511 34842 34).