Author Archives: Simon Jebsen

Writing Your Literature Review

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Sylvia Rohlfer (CUNEF University)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Regardless of discipline and however original a research project is, the literature review is a key part of a thesis or article. However, writing a literature review is the most daunting part of writing. Doctoral students often comment that the literature seems (and often is) massive. Hence, it might be helpful to be as systematic as possible when completing this task.

In this course, you will get practical insights and advice on how to effectively write a literature review. This will include tips, tricks and tools to improve your reading and sorting of the references, synthesizing the literature, summarizing existing debates and providing advice on how to present reviews effectively. We will also consider your writing habits. The sessions will be practical and require active involvement by students who will work in groups and get focused feedback on individual projects.

There are no pre-readings for the course, but participants will be required to complete smaller tasks outside the allotted workshop hours. Prior to the seminar (on or before the 28th of August) participants should send an extended abstract of their research project (two pages max. and in English/German/Spanish) to srohlfer@cunef.edu.

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

ReMaT – Research management training for early-stage researchers

A ReMaT workshop – Research management online training for early-stage researchers – will take place on 21st and 22nd October 2021. The workshop is designed for early-stage researchers in engineering and natural sciences, particularly PhD candidates from the 2nd year onwards. The idea of European networking is very much embedded in the concept, and we encourage participation from many different countries at the workshop.

ReMaT is an interactive, intensive workshop providing an introduction to research management. It involves two international trainers and is held in English. The modules of the workshop cover exploitation of knowledge and entrepreneurship, acquisition of grants, intellectual property rights and the management of interdisciplinary projects. They are delivered in such a way that it challenges participants to consider different perspectives on how they might use their PhD education in a variety of career paths, and convince others to hire them.

More information and registration

TUTECH INNOVATION GMBH which is organising the workshop was founded in 1992 as the technology transfer institute for the Hamburg University of Technology. We are offering services regarding participation in EU-funded programmes especially for publicly funded universities and SMEs.

Data Analysis with Stata

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tobias Gramlich, Hesse State Statistical Office

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Stata is a statistical program package widely used (not only) in the social and economic sciences; it is used for data management, statistical graphics and analysis of quantitative data. Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics. The course should enable participants to prepare their data for analysis, perform adequate analysis using a statistical computer program and document these tasks to keep them reproducible.

For Beginners with no or very little Stata knowledge!

Course topics cover:

  • “What You Type Is What You Get”: Basic Stata Command syntax
  • Getting (and Understanding) Help within Stata: Stata Built-in Help System
  • Basic Data Management: Load and Save Stata Datasets, Generate and Manipulate Variables, Describe and Label Data and Variables, Perform Basic uni- and bivariate Analyses, Change the Structure of your Data
  • Basic Stata Graphics: Scatterplot, Histogram, Bar Chart
  • Working with “Do-” and “Log-” Files

A requirement of students: Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics.

Recommended literature and pre-readings: None.

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

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.

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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.