BE INSPIRED

"The Graduate School provides vast resources for doctoral students, including a wide range of courses conducive to training and thesis work." Dominic Ponattu, CDSS

Spring 2021

Course Catalog

CDSS courses are open to GESS doctoral students as well as CDSS Associate Members only

Spring 2021


Course Type: core course

Course Content

Doctoral theses supervised by Henning Hillmann, Florian Keusch, Irena Kogan, Frauke Kreuter, and Katja Möhring respectively, will be discussed.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Tutorial
Keusch
10.02.20
25.05.20
Monday
15:30
17:00
tbd
Kogan
02.03.21
15.06.21
Tuesday
13:45
15:15
tbd
Gautschi
02.03.21
15.06.21
Tuesday
13:45
15:15
tbd
Hillmann
03.03.21
16.06.21
Wednesday
17:15
18:45
tbd
Möhring
04.03.21
17.06.21
Thursday
10:15
11:45
tbd

Lecturer(s)


Course Type: core course

Course Number: DIS

Credits: 2+8

Prerequisites

Crafting Social Science Research, Literature Review


Course Content

The goal of this course is to provide support and crucial feedback on writing students' dissertation proposal. Such a proposal is a research outline that delineates the doctoral thesis project, including the motivation for research question(s), the survey of the relevant theoretical and empirical contributions, the development of a theoretical framework, the specification of the methodology and planned empirical analysis.
You should be prepared to address the following questions: What makes that an interesting question? Is it an important question? What contributions would this question and the answers make to the scholarly literature? What strategies are there to answer your research question(s)?

Nota bene: Further meeting dates will be determined during the first session.

Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
1st meeting, further dates tbd
02.03.21
Tuesday
10:15
11:45
tbc

Lecturer(s)


Course Type: core course

Course Number: RES

Credits: 2 or 3 depending on applicable study regulations

Course Content

Participation is mandatory for first to third year CDSS Sociology students. Participation is recommended for later CDSS doctoral candidates, but to no credit.

The goal of this course is to provide support and crucial feedback for CDSS doctoral candidates in sociology on their ongoing dissertation project. In this workshop CDSS students are expected to play two roles. They should provide feedback to their peers as well as present their own work in order to receive feedback.

 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
01.03.21
14.06.21
Monday
14:00
15:00
Sowi Zoom 05

Lecturer(s)


Course Type: core course

Course Number: RES

Credits: 3

Prerequisites

CSSR, Literature Review


Course Content

The goal of this course is to provide guidance and constructive feedback on writing academic papers in English. Each session will guide students through techniques for writing and/or revision of a paper or other similar document. Between sessions, students will apply techniques learnt to their own texts, receiving frequent feedback on their papers and tips on how to improve their writing. By the end of the course each participant will have improved at least one paper to a publishable standard and should be able to approach their next paper with greater confidence.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
04.03.21
17.06.21
Thursday
12:00
13:30
Sowi Zoom 01


Course Type: core course

Course Number: RES

Credits: 2

Course Content

Please refer to the MZES webpages for dates and times.



Course Type: elective course

Course Number: MET

Credits: up to 12

Prerequisites

CDSS doctoral students have privileged access to the GESIS Summer School in Survey Methodology as well as GESIS workshops are exempt from course fees*.

Contact the Center Manager before registering for any of the courses and only thereafter register directly through the GESIS web page making sure to mention that you are a CDSS doctoral student.

The GESIS summer school takes place in Cologne from 28 July to 20 August 2021. Detailed information about the summer school program is available on the GESIS website.

 

 

 

*According to the provisions stated in §3 (5) of the GESIS CDSS cooperative treaty.



Course Type: elective course

Course Number: MET

Credits: 6+2

Prerequisites

Knowledge of Multivariate Analysis


Course Content

The goal of this course is to provide an introduction into maximum-likelihood estimation.

Students who wish to pass this course must complete homework assignments and produce a research paper. Participation in the tutorial session (2 ECTS) is mandatory for the assignments which complement the lecture (6 ECTS).

Course requirements & assessment

Homework assignements, final paper (graded)

 

Tutorial

This tutorial accompanies the course “Advanced Quantitative Methods” in Political Science. The lab sessions will focus on the practical issues associated with quantitative methods, including obtaining and preparing data sets, how to use statistical software, which tests to use for different kinds of problems, how to graph data effectively for presentation and analysis, and how to interpret results. The seminar will also serve as a software tutorial. No prior knowledge of statistical programming is expected.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Tutorial
04.03.21
17.06.21
Thursday
10:15
11:45
Sowi Zoom 06
Lecture
03.03.21
16.06.21
Wednesday
08:30
10:00
Sowi Zoom 01

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Course Content

In the wake of the digital revolution, societies store an ever-increasing amount of data on humans and their behavior. In parallel, advances in computational power & methods allow for meaningful interpretations of such data. This enables social scientists to approach old questions with new methods, but also to study entirely new questions.
The seminar introduces students to different aspects of this “big data revolution”. It comprises theoretical sessions in which discuss the implications such as the societal and scientific opportunities and challenges of new forms of data and methods (from social media, communications platforms, Internet of Things devices, sensors/wearables, and mobile phones, digitized old data records, machine learning). In addition, it comprises lab sessions in which we learn – hands-on – how such new forms of data can be captured, curated, and analyzed using computational methods. Students apply what they have learned in their own projects.  

Course requirements & assessment

  • Participation
  • Weekly reading and preparation of materials and exercises
  • (Individual) Presentation of the planned term paper towards the end of the term
  • Written term paper (graded)

Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
02.03.21
16.06.20
Tuesday
15:30
17:15
Sowi Zoom 02

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Course Content

Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of survey design. The course covers the major steps of implementing and conducting a survey and design decisions at each step. In addition, sources of error at each step are discussed. For illustration purposes and exercise, the course will draw on well-known large-scale surveys such as the German General Survey (ALLBUS), European Social Survey (ESS), European Values Study (EVS), and the German Socio-economic Panel (SOEP).

Course requirements & assessment

Active participation, homework assignments/oral presentations, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
04.03.21
17.06.21
Thursday
13:45
15:15
Sowi Zoom 04

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Prior experience with R is helpful, but not necessary. Optional learning resources can be found here: https://rstudio.cloud/learn/primers


Course Content

Machine Learning (ML) is increasingly used to guide high-stakes decisions in various contexts such as college admissions, granting loans or hiring employees. By eliminating human judgment, ML-based decision-making promises to be neutral and objective and to find the right decisions in shorter time. At the same time, however, concerns are raised that algorithmic decision-making may foster discrimination and amplify existing biases that are fed into the models. This course discusses recent advances in the field of Interpretable and Fair ML: How can we explain predictions of black-box models? How can we measure and mitigate biases to make ML models fair? In addition to covering fairness and interpretability, the course will include a general introduction to supervised machine learning. Hands-on lab sessions will demonstrate how to train and interpret ML models using R.

Course requirements & assessment:

Presentation and  term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
1st group
11.03.21
17.06.21
Thursday
13:45
15:15
Sowi Zoom 03
2nd group
16.04.21
28.05.21
Friday
12:00
15:15
Sowi Zoom 04

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6+3

Course Content

Lecture

The course provides a broad overview over methods of longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-sectional data, panel data can allow to improve causal inference. The first objective of this course is to understand why and under which conditions this is the case. In the next step, we will discuss a variety of different modeling approaches to panel data (fixed effects, random effects, first difference) and learn how to decide between these models. The lecture also provides an overview over event history models. It is highly recommended to participate in the parallel exercises to this lecture, in which the presented models are applied to real data sets.

Tutorial

Using Stata, we apply methods of longitudinal data analysis (especially first-difference-models, random/fixed effects-models, event history analysis) to real survey data. Attendance of the complementary lecture "Longitudinal Data Analysis" is highly recommended as firm knowledge of the lecture content is presumed. Some knowledge of Stata is helpful, but not required.
 

Course requirements & assessment

Successful participation in the tutorial (active participation, short oral presentation, short assignments (graded), written exam (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Tutorial
04.03.21
17.06.21
Thursday
12:00
13:30
Sowi Zoom 07
Lecture
04.03.21
17.06.21
Thursday
10:15
11:45
Sowi Zoom 07

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Regression analysis


Course Content

Multilevel modeling is used when observations on the individual level are nested in units of one or more higher levels (e.g. students in classes in schools). The course will cover the logic of multilevel modeling, its statistical background, and implementation with Stata. Applications will come from international comparative research treating countries as the higher level units. Data from the International Social Survey Program and the PIONEUR project (on intra-European migration) serve as examples. However, students are also encouraged to bring their own data.

Course requirements & assessment

Home assignments, presentation (graded)

Literature

  • Goldstein, H. (2010). Multilevel Statistical Models (Fourth Edition). London: Arnold.
  • Hox, J. (2010). Multilevel Analysis: Techniques and Applications. Mahwah, NJ: Erlbaum.
  • Rabe-Hesketh, S. & Skrondal, A. (2012). Multilevel and Longitudinal Modeling Using Stata. 3nd Edition. College Station, TX: Stata Press.
  • Raudenbush, S. W. & Bryk, A. S. (2002). Hierarchical Linear Models. Thousand Oaks: Sage.
  • Snijders, T. A. B. & Bosker, R. J. (2012). Multilevel Analysis. An Introduction to Basic and Advanced Multilevel Modelling. London: Sage.
  • StataCorp. (2017). Stata Multilevel Mixed-Effects. Reference Manual. Release 15. College Station, TX: Stata Press.

Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
03.03.21
24.03.21
Wednesday
13:45
17:00
Sowi Zoom 14
05.05.21
Wednesday
13:45
17:00
Sowi Zoom 14
19.05.21
Wednesday
13:45
17:00
Sowi Zoom 14
09.06.21
Wednesday
13:45
17:00
Sowi Zoom 14


Course Type: elective course

Course Number: MET

Course Content

SMiP web page with full details

SMiP courses open to CDSS doctoral students:

Foundations 2: Modeling Intraindividual Variabilty and Change, 12 & 19 April
Foundations 2: Stochastic Models of Time-Dependent Cognitive Mechanisms,
30 April & 11 June
Foundations 2: Multinomial-Processing-Tree (MPT) Modeling: Basic Methods and Recent Advances, dates tba

Advanced topics in browser-based experimentation, 22 March – 25 March 2021 (3:30 p.m. – 5:30 p.m.) and 23 April 2021 (1 p.m. – 6 p.m.)

Multiverse Analysis: Taming Modelers’ Many Degrees of Freedom, 26 March (9 am – 5 pm) and 29 April 2021 (1:45 pm – 5 pm)

Advanced topics in R, 9 April 2021 (9 am – 5 pm)

Basic Concepts of Stochastic Processes, 15 &16 April 2021 (9 am – 5 pm)

Hands-on Open Science, 6 May 2021 (9 am – 5 pm)

Bridge sampling: An efficient method to approach inequality constrained hypotheses, 7 May 2021 (9 am – 5 pm)

Two-Process-Theories: An overview, 12 May 2021 (9 am – 5 pm)

IRT Modeling – Theory and Applications in R **, TBA May (9 am – 5 pm)

Multilevel Structural Equation Modeling, 14 June – 16 June 2021 (5 pm – 9 pm)

Modern R, 06 July 2021 (9 am – 5 pm)

 

Please register by sending an e-mail to Annette Förster.

 



Course Type: elective course

Course Number: MET/POL

Credits: 8

Prerequisites

Topics covered in introductory Game Theory class


Course Content

This course is a continuation of the intro into Game Theory and surveys key applications of game theory with a particular emphasis on the link of theories, methods and empirics. Emphasis will be placed on prominent applications of those concepts in political science, in both comparative and international politics. Topics covered include electoral competition, delegation, political agency, governmental veto players, authoritarian politics, manipulation, war and crisis bargaining. While the focus is on understanding applied work, previous training in game theory is required. Students will build upon their previous game theory training to become informed consumers of scholarship utilizing the methodology and begin to learn how to apply game-theoretic logic to their own work. The course is partly taught from lecture notes, at other times students present a research paper and stimulate discussion in class.

Course requirements & assessment

Class discussion, paper presentation, participation, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
01.03.21
14.06.21
Monday
15:30
17:00
Sowi Zoom 07


Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

lab.js is a simple, graphical tool to help you build studies for the web and the laboratory – in addition, it is free and open-source. Many standard tasks can be implemented in lab.js  using its graphical user interface. In addition, more complex tasks can be realized through the underlying programming language JavaScript. The goal of the workshop is to provide an introduction to both approaches. In doing so, the workshop involves both structured input from the instructor as well as a number of practical exercises so that participants can directly explore the features of lab.js. No prior knowledge of the software or JavaScript is required. As an assignment, participants will create their own experiment based on the requirements discussed in the workshop.

Course requirements & assessment

As an assignment (graded), participants will create their own experiment based on the requirements discussed in the workshop.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
16.04.21
23.04.21
Friday
10:15
15:15
Sowi Zoom 12
17.04.21
24.04.21
Saturday
10:15
17:00
Sowi Zoom 12


Course Type: elective course

Course Number: RES

Credits: 5

Prerequisites

This course is exclusively geared towards students who are currently doctoral students at the GESS of the University of Mannheim. It is intended for beginning as well as advanced doctoral students. This course is an elective course and counts as a 'Bridge Course'. Maximum number of participants is 15. If the course is not fully booked, non-GESS students from Business, Economics, or the Social Sciences or from other related disciplines can enroll.


Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS. This year, the course will be given by one senior researchers from each center of the GESS, i.e., you will have the unique opportunity to receive truly interdisciplinary feedback on your work from three different angles.  

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by the instructors, each participant will shortly (max 5 min, 2-3 slides per person) present the core idea of an interdisciplinary paper published in a top journal in her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. Mini Research Day

The second component of the course is a ‘Mini-Research-Day’ which is intended to introduce the kind of topics you are working on to the other participants. You will give a presentation on a current working paper or research project of yours and you will discuss a paper/presentation from one of your fellow students from another field (10 min presentation, 5 min discussion, 10 min Q&A).

3. Science Speed Dating

The science speed dating event - organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a student from another field (preferably from our course).

4. Project Presentations & Writeups

This proposal will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in two weeks after the presentation.

Course requirements & assessment

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in the ‘Mini Research Day’. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant 10 days before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Course dates

  • March 11th, 2021, 12.30-3.30pm, Kick-Off Meeting
  • April 12th, 2021 - Deadline to send paper to discussant (and in cc: to gess@uni-  mannheim.de)
  • April 22th, 2021 – Mini Research Day (whole day symposium)
  • April 28th, time tba - Science Speed Dating Event
  • May 28th, 2021, Presentation of research proposal (half- to full day symposium)
  • June 13th, 2021 - Deadline to hand in interdisciplinary research proposal (to: gess@uni-mannheim.de)

Competences acquired

Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have received feedback from senior researchers from all three centers.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Lecturer(s)


Course Type: elective course

Course Number: SOC

Credits: 6

Course Content

This advanced seminar will explore recent social science research that seeks to explain variation in career opportunities within organizations and career mobility between organizations. We will consider a variety of research questions: what kinds of changes do we observe in career paths over time? How much of the change can be attributed to the variation in experience between different cohorts of workers? How much of the change in career patterns is due to organizational change within firms? How does matching between labor demand and supply work in different occupational settings? What are the underlying mechanisms that channel mobility within and between organizations? To what extent are skills transferable from one job to the next? How do new occupations and professions emerge and establish themselves? To address these and further questions, we will rely both on recent theoretical advances and on empirical studies in various settings.

Course requirements & assessment

Active participation, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
02.03.21
15.06.21
Tuesday
12:00
13:30
Sowi Zoom 01


Course Type: elective course

Course Number: SOC

Credits: 6

Course Content

This seminar deals with identity, religion, and intergroup relations. Broadly speaking, we will start by focusing on mechanisms that drive the development of ethnic, national, and religious identities and end by examining the ways in which these identities affect intergroup attitudes and behavior.
In the first half of the seminar, we will introduce the concept of social identity and its theoretical foundations and implications. We will discuss the development and peculiarities of ethnic, national, and religious identities. Reading both conceptual and empirical papers, we are particularly interested in how identity development is shaped by intergroup relations. Considering the perspective of both minority and majority group members, we will examine how minority members react to perceived discrimination as well as what attitudes majority group members hold towards members of different minority groups.
In the second half of the seminar, we will ask how identities affect intergroup relations and discuss empirical studies on intergroup attitudes and friendship. In the final weeks, participants will develop an own research idea that will result in a term paper. The term paper has to be submitted after the end of the seminar, and it can be either an empirical study or a theoretical elaboration. To facilitate the writing of the term papers, students will present and discuss each other’s ideas in the last weeks in class.

Course requirements & assessment

Participation, weekly reading and preparation of materials; (Group) Presentation of an empirical study; ) (Individual) Presentation of the planned term paper towards the end of the term. Submission of written term paper (after the seminar ended, graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
04.03.21
17.06.21
Thursday
15:30
17:00
Sowi Zoom 07

Lecturer(s)


Course Type: elective course

Course Number: SOC

Credits: 6

Course Content

In the age of increasing migration and the raise of right-wing populist parties the question of how to measure and explain xenophobic and populist attitudes becomes very important. While xenophobia has already been investigated for a long time, even if it still constitutes a controversial issue how to measure it, research on populist attitudes has started only very recently. In this seminar current and innovative approaches as well as ideas for further developments will be discussed. Moreover, existing studies will be replicated to explore them more deeply.

Course requirements & assessment

Participation, weekly reading, presentation of an empirical study, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
04.03.21
17.06.21
Thursday
08:30
10:00
Sowi Zoom 03

Lecturer(s)


Course Type: elective course

Course Number: SOC

Credits: 6

Course Content

Poverty and social exclusion are extreme forms of inequality in modern societies. In Europe, these phenomena show up in different forms and imply different consequences for the people at risk. The seminar will provide an introduction into various concepts, dimensions and measures of poverty and social conclusion. We will discuss theories on the causes of poverty and social exclusion, learn about different policies throughout Europe to lower poverty, and we will study consequences of poverty in various domains.

Course requirements & assessment

Regular small assignments (developing research questions based on the readings), participating in active discussion. Written term paper (max. 5000 words, graded), deadline: Aug 31, 2021

Course dates

March 3, 17 and 24

April 14 and 28

May 12

June 9

Wednesday from 8.30 to 11.45am

Room Sowi Zoom 15


Lecturer(s)


Course Type: core course

Course Number: DIS

Credits: 2+8

Prerequisites

Crafting Social Science Research, Literature Review


Course Content

The goal of this course is to provide support and crucial feedback on writing students' dissertation proposal. Such a proposal is a research outline that delineates the doctoral thesis project, including the motivation for research question(s), the survey of the relevant theoretical and empirical contributions, the development of a theoretical framework, the specification of the methodology and planned empirical analysis.
You should be prepared to address the following questions: What makes that an interesting question? Is it an important question? What contributions would this question and the answers make to the scholarly literature? What strategies are there to answer your research question(s)?

Nota bene: Further meeting dates will be determined during the first session.

Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
1st meeting, further dates tbd
02.03.21
Tuesday
10:15
11:45
tbc


Course Type: core course

Course Number: MET

Credits: 6+2

Prerequisites

Knowledge of Multivariate Analysis


Course Content

The goal of this course is to provide an introduction into maximum-likelihood estimation.

Students who wish to pass this course must complete homework assignments and produce a research paper. Participation in the tutorial session (2 ECTS) is mandatory for the assignments which complement the lecture (6 ECTS).

Course requirements & assessment

Homework assignements, final paper (graded)

 

Tutorial

This tutorial accompanies the course “Advanced Quantitative Methods” in Political Science. The lab sessions will focus on the practical issues associated with quantitative methods, including obtaining and preparing data sets, how to use statistical software, which tests to use for different kinds of problems, how to graph data effectively for presentation and analysis, and how to interpret results. The seminar will also serve as a software tutorial. No prior knowledge of statistical programming is expected.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Tutorial
04.03.21
17.06.21
Thursday
10:15
11:45
Sowi Zoom 06
Lecture
03.03.21
16.06.21
Wednesday
08:30
10:00
Sowi Zoom 01

Lecturer(s)


Course Type: core course

Course Number: RES

Credits: 2 or 3 depending on applicable study regulations

Course Content

Participation is mandatory for first to third year CDSS students of Political Science. Participation is recommended for later CDSS PhD candidates, but to no credit.

Other young researchers in the social sciences affiliated with the University of Mannheim (incl. MZES and SFB 884) are also invited to attend the talks.

The goal of this course is to provide support and crucial feedback for CDSS doctoral students on their ongoing dissertation project. In this workshop they are expected to play two roles - provide feedback to their peers as well as present their own work in order to receive feedback.

In order to receive useful feedback, participants are asked to circulate their paper and two related published pieces of research one week before the talk.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
03.03.21
16.06.21
Wednesday
12:00
13:30
Sowi Zoom 01

Lecturer(s)


Course Type: core course

Course Number: RES

Credits: 3

Prerequisites

CSSR, Literature Review


Course Content

The goal of this course is to provide guidance and constructive feedback on writing academic papers in English. Each session will guide students through techniques for writing and/or revision of a paper or other similar document. Between sessions, students will apply techniques learnt to their own texts, receiving frequent feedback on their papers and tips on how to improve their writing. By the end of the course each participant will have improved at least one paper to a publishable standard and should be able to approach their next paper with greater confidence.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
04.03.21
17.06.21
Thursday
12:00
13:30
Sowi Zoom 01


Course Type: core course

Course Number: RES

Credits: 2

Course Content

Please refer to the MZES webpages for dates and times.



Course Type: core course

Course Number: RES

Credits: 2

Prerequisites

CSSR, TBCI, Dissertation Proposal


Course Content

Attending the Seminar Series on the Political Economy of Reforms is a possible alternative to attending the MZES B colloquium. Please refer to the SFB 884 website for dates and times.



Course Type: elective course

Course Number: MET

Credits: up to 12

Prerequisites

CDSS doctoral students have privileged access to the GESIS Summer School in Survey Methodology as well as GESIS workshops are exempt from course fees*.

Contact the Center Manager before registering for any of the courses and only thereafter register directly through the GESIS web page making sure to mention that you are a CDSS doctoral student.

The GESIS summer school takes place in Cologne from 28 July to 20 August 2021. Detailed information about the summer school program is available on the GESIS website.

 

 

 

*According to the provisions stated in §3 (5) of the GESIS CDSS cooperative treaty.


Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Course Content

In the wake of the digital revolution, societies store an ever-increasing amount of data on humans and their behavior. In parallel, advances in computational power & methods allow for meaningful interpretations of such data. This enables social scientists to approach old questions with new methods, but also to study entirely new questions.
The seminar introduces students to different aspects of this “big data revolution”. It comprises theoretical sessions in which discuss the implications such as the societal and scientific opportunities and challenges of new forms of data and methods (from social media, communications platforms, Internet of Things devices, sensors/wearables, and mobile phones, digitized old data records, machine learning). In addition, it comprises lab sessions in which we learn – hands-on – how such new forms of data can be captured, curated, and analyzed using computational methods. Students apply what they have learned in their own projects.  

Course requirements & assessment

  • Participation
  • Weekly reading and preparation of materials and exercises
  • (Individual) Presentation of the planned term paper towards the end of the term
  • Written term paper (graded)

Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
02.03.21
16.06.20
Tuesday
15:30
17:15
Sowi Zoom 02

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Course Content

Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of survey design. The course covers the major steps of implementing and conducting a survey and design decisions at each step. In addition, sources of error at each step are discussed. For illustration purposes and exercise, the course will draw on well-known large-scale surveys such as the German General Survey (ALLBUS), European Social Survey (ESS), European Values Study (EVS), and the German Socio-economic Panel (SOEP).

Course requirements & assessment

Active participation, homework assignments/oral presentations, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
04.03.21
17.06.21
Thursday
13:45
15:15
Sowi Zoom 04

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Prior experience with R is helpful, but not necessary. Optional learning resources can be found here: https://rstudio.cloud/learn/primers


Course Content

Machine Learning (ML) is increasingly used to guide high-stakes decisions in various contexts such as college admissions, granting loans or hiring employees. By eliminating human judgment, ML-based decision-making promises to be neutral and objective and to find the right decisions in shorter time. At the same time, however, concerns are raised that algorithmic decision-making may foster discrimination and amplify existing biases that are fed into the models. This course discusses recent advances in the field of Interpretable and Fair ML: How can we explain predictions of black-box models? How can we measure and mitigate biases to make ML models fair? In addition to covering fairness and interpretability, the course will include a general introduction to supervised machine learning. Hands-on lab sessions will demonstrate how to train and interpret ML models using R.

Course requirements & assessment:

Presentation and  term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
1st group
11.03.21
17.06.21
Thursday
13:45
15:15
Sowi Zoom 03
2nd group
16.04.21
28.05.21
Friday
12:00
15:15
Sowi Zoom 04

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6+3

Course Content

Lecture

The course provides a broad overview over methods of longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-sectional data, panel data can allow to improve causal inference. The first objective of this course is to understand why and under which conditions this is the case. In the next step, we will discuss a variety of different modeling approaches to panel data (fixed effects, random effects, first difference) and learn how to decide between these models. The lecture also provides an overview over event history models. It is highly recommended to participate in the parallel exercises to this lecture, in which the presented models are applied to real data sets.

Tutorial

Using Stata, we apply methods of longitudinal data analysis (especially first-difference-models, random/fixed effects-models, event history analysis) to real survey data. Attendance of the complementary lecture "Longitudinal Data Analysis" is highly recommended as firm knowledge of the lecture content is presumed. Some knowledge of Stata is helpful, but not required.
 

Course requirements & assessment

Successful participation in the tutorial (active participation, short oral presentation, short assignments (graded), written exam (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Tutorial
04.03.21
17.06.21
Thursday
12:00
13:30
Sowi Zoom 07
Lecture
04.03.21
17.06.21
Thursday
10:15
11:45
Sowi Zoom 07

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Regression analysis


Course Content

Multilevel modeling is used when observations on the individual level are nested in units of one or more higher levels (e.g. students in classes in schools). The course will cover the logic of multilevel modeling, its statistical background, and implementation with Stata. Applications will come from international comparative research treating countries as the higher level units. Data from the International Social Survey Program and the PIONEUR project (on intra-European migration) serve as examples. However, students are also encouraged to bring their own data.

Course requirements & assessment

Home assignments, presentation (graded)

Literature

  • Goldstein, H. (2010). Multilevel Statistical Models (Fourth Edition). London: Arnold.
  • Hox, J. (2010). Multilevel Analysis: Techniques and Applications. Mahwah, NJ: Erlbaum.
  • Rabe-Hesketh, S. & Skrondal, A. (2012). Multilevel and Longitudinal Modeling Using Stata. 3nd Edition. College Station, TX: Stata Press.
  • Raudenbush, S. W. & Bryk, A. S. (2002). Hierarchical Linear Models. Thousand Oaks: Sage.
  • Snijders, T. A. B. & Bosker, R. J. (2012). Multilevel Analysis. An Introduction to Basic and Advanced Multilevel Modelling. London: Sage.
  • StataCorp. (2017). Stata Multilevel Mixed-Effects. Reference Manual. Release 15. College Station, TX: Stata Press.

Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
03.03.21
24.03.21
Wednesday
13:45
17:00
Sowi Zoom 14
05.05.21
Wednesday
13:45
17:00
Sowi Zoom 14
19.05.21
Wednesday
13:45
17:00
Sowi Zoom 14
09.06.21
Wednesday
13:45
17:00
Sowi Zoom 14


Course Type: elective course

Course Number: MET

Course Content

SMiP web page with full details

SMiP courses open to CDSS doctoral students:

Foundations 2: Modeling Intraindividual Variabilty and Change, 12 & 19 April
Foundations 2: Stochastic Models of Time-Dependent Cognitive Mechanisms,
30 April & 11 June
Foundations 2: Multinomial-Processing-Tree (MPT) Modeling: Basic Methods and Recent Advances, dates tba

Advanced topics in browser-based experimentation, 22 March – 25 March 2021 (3:30 p.m. – 5:30 p.m.) and 23 April 2021 (1 p.m. – 6 p.m.)

Multiverse Analysis: Taming Modelers’ Many Degrees of Freedom, 26 March (9 am – 5 pm) and 29 April 2021 (1:45 pm – 5 pm)

Advanced topics in R, 9 April 2021 (9 am – 5 pm)

Basic Concepts of Stochastic Processes, 15 &16 April 2021 (9 am – 5 pm)

Hands-on Open Science, 6 May 2021 (9 am – 5 pm)

Bridge sampling: An efficient method to approach inequality constrained hypotheses, 7 May 2021 (9 am – 5 pm)

Two-Process-Theories: An overview, 12 May 2021 (9 am – 5 pm)

IRT Modeling – Theory and Applications in R **, TBA May (9 am – 5 pm)

Multilevel Structural Equation Modeling, 14 June – 16 June 2021 (5 pm – 9 pm)

Modern R, 06 July 2021 (9 am – 5 pm)

 

Please register by sending an e-mail to Annette Förster.

 



Course Type: elective course

Course Number: MET/POL

Credits: 8

Prerequisites

Topics covered in introductory Game Theory class


Course Content

This course is a continuation of the intro into Game Theory and surveys key applications of game theory with a particular emphasis on the link of theories, methods and empirics. Emphasis will be placed on prominent applications of those concepts in political science, in both comparative and international politics. Topics covered include electoral competition, delegation, political agency, governmental veto players, authoritarian politics, manipulation, war and crisis bargaining. While the focus is on understanding applied work, previous training in game theory is required. Students will build upon their previous game theory training to become informed consumers of scholarship utilizing the methodology and begin to learn how to apply game-theoretic logic to their own work. The course is partly taught from lecture notes, at other times students present a research paper and stimulate discussion in class.

Course requirements & assessment

Class discussion, paper presentation, participation, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
01.03.21
14.06.21
Monday
15:30
17:00
Sowi Zoom 07


Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

lab.js is a simple, graphical tool to help you build studies for the web and the laboratory – in addition, it is free and open-source. Many standard tasks can be implemented in lab.js  using its graphical user interface. In addition, more complex tasks can be realized through the underlying programming language JavaScript. The goal of the workshop is to provide an introduction to both approaches. In doing so, the workshop involves both structured input from the instructor as well as a number of practical exercises so that participants can directly explore the features of lab.js. No prior knowledge of the software or JavaScript is required. As an assignment, participants will create their own experiment based on the requirements discussed in the workshop.

Course requirements & assessment

As an assignment (graded), participants will create their own experiment based on the requirements discussed in the workshop.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
16.04.21
23.04.21
Friday
10:15
15:15
Sowi Zoom 12
17.04.21
24.04.21
Saturday
10:15
17:00
Sowi Zoom 12

Lecturer(s)


Course Type: elective course

Course Number: POL

Credits: 6

Course Content

The main goal of this lecture is to present an advanced introduction to theoretical approaches, key concepts, and substantive issues in comparative political behavior. Building on a multi-level perspective, it will provide an overview of key concepts and theories in the analysis of micro-level processes of political behavior that are embedded in and feed into macro-level processes. Capitalizing on this analytical perspective, the lecture will also address major changes in the relationship between societal and political processes and institutions.

Course requirements & assessment

Term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
01.03.21
14.06.21
Monday
10:15
11:45
Sowi Zoom 01

Lecturer(s)


Course Type: elective course

Course Number: POL

Credits: 6

Course Content

This lecture offers an introduction to current research topics in the field of International Political Economy (IPE). It examines how international and domestic politics interact with global flows of goods, finance, and people across national borders. After introducing what it means to study IPE in the age of globalization, the course addresses four major themes of current IPE research. We will learn about internationale trade and the chances and challenges that come with the intensifying exchange of goods across the globe. Lectures on international finance will focus on how global financial flows interact with political and economic stability, instability, and crises. We will also focus on international development and will learn about patterns of global economic inequality and development aid. The lecture will also adress the role of international institutions for the globalized economy.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.03.21
16.06.21
Wednesday
10:15
11:45
Sowi Zoom 02


Course Type: elective course

Course Number: POL

Credits: 8

Course Content

To openly express one’s views and the freedom to obtain and share information are the mostfundamental civil liberties. While they are under constant and serious threat in authoritarian contexts, the question of how free speech should be regulated is also a concern in liberal democracies. The aim of this course is to discuss contemporary scholarly research on the politics of free speech and censorship. Why is free expression so important? Why and how do states actually censor and regulate free speech. And what are the direct, the political and the unintended effects of censorship and speech regulation? How do social media and the digital revolution impact on these questions? Next to substantive discussion the course will place great emphasis on the practice of quantitative political research.

Course requirements & assessment

Active participation


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
04.03.21
17.06.21
Thursday
13:45
15:15
Sowi Zoom 05

Lecturer(s)


Course Type: elective course

Course Number: POL

Credits: 8

Course Content

This seminar discusses seminal and current work on state repression, security and peace. It introduces on why and how states violate human rights. It focuses on how governments organize and implement repression and how they aim to justify or obfuscate state violence, particularly in the context of democratic institutions and international human rights norms. The discussion also discusses peace as a more heterogenous concept than the absence of war. Over the course of the seminar you will develop your own research question on one of the topics discussed in the seminar and carrying out your own research. Additionally, you are expected to read all required materials, provide feedback on other student’s work and lead one class discussion.

Course requirements & assessment

  • Participation: Discussion and analysis of academic literature, development and discussion of research questions, group discussions
  • Presentation: Critical literature review
  • Discussion of another student’s research proposal
  • Written research proposal
  • Research paper (graded)

 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
02.03.21
15.06.21
Tuesday
13:45
15:15
Sowi Zoom 02


Course Type: elective course

Course Number: RES

Credits: 5

Prerequisites

This course is exclusively geared towards students who are currently doctoral students at the GESS of the University of Mannheim. It is intended for beginning as well as advanced doctoral students. This course is an elective course and counts as a 'Bridge Course'. Maximum number of participants is 15. If the course is not fully booked, non-GESS students from Business, Economics, or the Social Sciences or from other related disciplines can enroll.


Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS. This year, the course will be given by one senior researchers from each center of the GESS, i.e., you will have the unique opportunity to receive truly interdisciplinary feedback on your work from three different angles.  

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by the instructors, each participant will shortly (max 5 min, 2-3 slides per person) present the core idea of an interdisciplinary paper published in a top journal in her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. Mini Research Day

The second component of the course is a ‘Mini-Research-Day’ which is intended to introduce the kind of topics you are working on to the other participants. You will give a presentation on a current working paper or research project of yours and you will discuss a paper/presentation from one of your fellow students from another field (10 min presentation, 5 min discussion, 10 min Q&A).

3. Science Speed Dating

The science speed dating event - organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a student from another field (preferably from our course).

4. Project Presentations & Writeups

This proposal will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in two weeks after the presentation.

Course requirements & assessment

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in the ‘Mini Research Day’. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant 10 days before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Course dates

  • March 11th, 2021, 12.30-3.30pm, Kick-Off Meeting
  • April 12th, 2021 - Deadline to send paper to discussant (and in cc: to gess@uni-  mannheim.de)
  • April 22th, 2021 – Mini Research Day (whole day symposium)
  • April 28th, time tba - Science Speed Dating Event
  • May 28th, 2021, Presentation of research proposal (half- to full day symposium)
  • June 13th, 2021 - Deadline to hand in interdisciplinary research proposal (to: gess@uni-mannheim.de)

Competences acquired

Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have received feedback from senior researchers from all three centers.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Lecturer(s)


Course Type: core course

Course Number: DIS

Credits: 2+8

Prerequisites

Crafting Social Science Research, Literature Review


Course Content

The goal of this course is to provide support and crucial feedback on writing students' dissertation proposal. Such a proposal is a research outline that delineates the doctoral thesis project, including the motivation for research question(s), the survey of the relevant theoretical and empirical contributions, the development of a theoretical framework, the specification of the methodology and planned empirical analysis.
You should be prepared to address the following questions: What makes that an interesting question? Is it an important question? What contributions would this question and the answers make to the scholarly literature? What strategies are there to answer your research question(s)?

Nota bene: Further meeting dates will be determined during the first session.

Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
1st meeting, further dates tbd
02.03.21
Tuesday
10:15
11:45
tbc


Course Type: core course

Course Number: RES

Credits: 2

Prerequisites

TCBI, CSSR, Dissertation Proposal


Course Content

Please check with individual chairs in the Psychology department for dates and times of research colloquia.

 

 


Lecturer(s)


Course Type: core course

Course Number: RES

Credits: 2

Course Content

We invite CDSS candidates to discuss their research with experts in the field. The chair of Clinical Psychology and Biological Psychology and Psychotherapy pursues a wide range of topics and brings together a large spectrum of research approaches. We address open questions regarding each step of creative research and prolific publication of our scientific results. Each week we select one or two of our own projects for discussion.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
07.09.21
07.12.21
Tuesday
08:30
10:00
tbc


Course Type: core course

Course Number: RES

Credits: 2 or 3 depending on applicable study regulations

Course Content

Participation is mandatory for first to third year CDSS doctoral students of Psychology. Participation is recommended for later CDSS doctoral students, but to no credit.

Research in Cognitive Psychology: Research projects in cognitive psychology and neuropsychology are planned, conducted, analyzed, and discussed.

 Application via 'Studierendenportal' is necessary to have access to the course material provided in ILIAS.

Open office hours:
Prof. Dr. Erdfelder: Thursday, 10.15h - 11.45h.


Literature: References will be given during the course.

Talk schedule


Competences acquired

Improvement in research skills and communication of research results.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
01.03.21
14.06.21
Monday
15:30
17:00
Sowi Zoom 14

Lecturer(s)


Course Type: core course

Course Number: RES

Credits: 3

Prerequisites

CSSR, Literature Review


Course Content

The goal of this course is to provide guidance and constructive feedback on writing academic papers in English. Each session will guide students through techniques for writing and/or revision of a paper or other similar document. Between sessions, students will apply techniques learnt to their own texts, receiving frequent feedback on their papers and tips on how to improve their writing. By the end of the course each participant will have improved at least one paper to a publishable standard and should be able to approach their next paper with greater confidence.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
04.03.21
17.06.21
Thursday
12:00
13:30
Sowi Zoom 01

Lecturer(s)


Course Type: core course

Course Number: RES

Credits: 2

Course Content

This course provides guidance, tools, and skills for/in English academic writing. The focus will be on writing and publishing articles in psychological journals. Important general techniques for writing will be discussed (and practiced in the form of exercises and writing assignments). Publication strategies, issues of journal selection, how to deal with reviews, and the usual “paperwork” (cover letter, revision letter etc) will also be covered.

Dates

9 (10am to 6pm) and 10 (9am to 5pm)  July 2021 in Mannheim or Landau



Course Type: elective course

Course Number: MET

Credits: up to 12

Prerequisites

CDSS doctoral students have privileged access to the GESIS Summer School in Survey Methodology as well as GESIS workshops are exempt from course fees*.

Contact the Center Manager before registering for any of the courses and only thereafter register directly through the GESIS web page making sure to mention that you are a CDSS doctoral student.

The GESIS summer school takes place in Cologne from 28 July to 20 August 2021. Detailed information about the summer school program is available on the GESIS website.

 

 

 

*According to the provisions stated in §3 (5) of the GESIS CDSS cooperative treaty.



Course Type: elective course

Course Number: MET

Credits: 6+2

Prerequisites

Knowledge of Multivariate Analysis


Course Content

The goal of this course is to provide an introduction into maximum-likelihood estimation.

Students who wish to pass this course must complete homework assignments and produce a research paper. Participation in the tutorial session (2 ECTS) is mandatory for the assignments which complement the lecture (6 ECTS).

Course requirements & assessment

Homework assignements, final paper (graded)

 

Tutorial

This tutorial accompanies the course “Advanced Quantitative Methods” in Political Science. The lab sessions will focus on the practical issues associated with quantitative methods, including obtaining and preparing data sets, how to use statistical software, which tests to use for different kinds of problems, how to graph data effectively for presentation and analysis, and how to interpret results. The seminar will also serve as a software tutorial. No prior knowledge of statistical programming is expected.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Tutorial
04.03.21
17.06.21
Thursday
10:15
11:45
Sowi Zoom 06
Lecture
03.03.21
16.06.21
Wednesday
08:30
10:00
Sowi Zoom 01

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Course Content

In the wake of the digital revolution, societies store an ever-increasing amount of data on humans and their behavior. In parallel, advances in computational power & methods allow for meaningful interpretations of such data. This enables social scientists to approach old questions with new methods, but also to study entirely new questions.
The seminar introduces students to different aspects of this “big data revolution”. It comprises theoretical sessions in which discuss the implications such as the societal and scientific opportunities and challenges of new forms of data and methods (from social media, communications platforms, Internet of Things devices, sensors/wearables, and mobile phones, digitized old data records, machine learning). In addition, it comprises lab sessions in which we learn – hands-on – how such new forms of data can be captured, curated, and analyzed using computational methods. Students apply what they have learned in their own projects.  

Course requirements & assessment

  • Participation
  • Weekly reading and preparation of materials and exercises
  • (Individual) Presentation of the planned term paper towards the end of the term
  • Written term paper (graded)

Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
02.03.21
16.06.20
Tuesday
15:30
17:15
Sowi Zoom 02

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Course Content

Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of survey design. The course covers the major steps of implementing and conducting a survey and design decisions at each step. In addition, sources of error at each step are discussed. For illustration purposes and exercise, the course will draw on well-known large-scale surveys such as the German General Survey (ALLBUS), European Social Survey (ESS), European Values Study (EVS), and the German Socio-economic Panel (SOEP).

Course requirements & assessment

Active participation, homework assignments/oral presentations, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
04.03.21
17.06.21
Thursday
13:45
15:15
Sowi Zoom 04

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Prior experience with R is helpful, but not necessary. Optional learning resources can be found here: https://rstudio.cloud/learn/primers


Course Content

Machine Learning (ML) is increasingly used to guide high-stakes decisions in various contexts such as college admissions, granting loans or hiring employees. By eliminating human judgment, ML-based decision-making promises to be neutral and objective and to find the right decisions in shorter time. At the same time, however, concerns are raised that algorithmic decision-making may foster discrimination and amplify existing biases that are fed into the models. This course discusses recent advances in the field of Interpretable and Fair ML: How can we explain predictions of black-box models? How can we measure and mitigate biases to make ML models fair? In addition to covering fairness and interpretability, the course will include a general introduction to supervised machine learning. Hands-on lab sessions will demonstrate how to train and interpret ML models using R.

Course requirements & assessment:

Presentation and  term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
1st group
11.03.21
17.06.21
Thursday
13:45
15:15
Sowi Zoom 03
2nd group
16.04.21
28.05.21
Friday
12:00
15:15
Sowi Zoom 04

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6+3

Course Content

Lecture

The course provides a broad overview over methods of longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-sectional data, panel data can allow to improve causal inference. The first objective of this course is to understand why and under which conditions this is the case. In the next step, we will discuss a variety of different modeling approaches to panel data (fixed effects, random effects, first difference) and learn how to decide between these models. The lecture also provides an overview over event history models. It is highly recommended to participate in the parallel exercises to this lecture, in which the presented models are applied to real data sets.

Tutorial

Using Stata, we apply methods of longitudinal data analysis (especially first-difference-models, random/fixed effects-models, event history analysis) to real survey data. Attendance of the complementary lecture "Longitudinal Data Analysis" is highly recommended as firm knowledge of the lecture content is presumed. Some knowledge of Stata is helpful, but not required.
 

Course requirements & assessment

Successful participation in the tutorial (active participation, short oral presentation, short assignments (graded), written exam (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Tutorial
04.03.21
17.06.21
Thursday
12:00
13:30
Sowi Zoom 07
Lecture
04.03.21
17.06.21
Thursday
10:15
11:45
Sowi Zoom 07

Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6

Prerequisites

Regression analysis


Course Content

Multilevel modeling is used when observations on the individual level are nested in units of one or more higher levels (e.g. students in classes in schools). The course will cover the logic of multilevel modeling, its statistical background, and implementation with Stata. Applications will come from international comparative research treating countries as the higher level units. Data from the International Social Survey Program and the PIONEUR project (on intra-European migration) serve as examples. However, students are also encouraged to bring their own data.

Course requirements & assessment

Home assignments, presentation (graded)

Literature

  • Goldstein, H. (2010). Multilevel Statistical Models (Fourth Edition). London: Arnold.
  • Hox, J. (2010). Multilevel Analysis: Techniques and Applications. Mahwah, NJ: Erlbaum.
  • Rabe-Hesketh, S. & Skrondal, A. (2012). Multilevel and Longitudinal Modeling Using Stata. 3nd Edition. College Station, TX: Stata Press.
  • Raudenbush, S. W. & Bryk, A. S. (2002). Hierarchical Linear Models. Thousand Oaks: Sage.
  • Snijders, T. A. B. & Bosker, R. J. (2012). Multilevel Analysis. An Introduction to Basic and Advanced Multilevel Modelling. London: Sage.
  • StataCorp. (2017). Stata Multilevel Mixed-Effects. Reference Manual. Release 15. College Station, TX: Stata Press.

Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
03.03.21
24.03.21
Wednesday
13:45
17:00
Sowi Zoom 14
05.05.21
Wednesday
13:45
17:00
Sowi Zoom 14
19.05.21
Wednesday
13:45
17:00
Sowi Zoom 14
09.06.21
Wednesday
13:45
17:00
Sowi Zoom 14


Course Type: elective course

Course Number: MET

Course Content

SMiP web page with full details

SMiP courses open to CDSS doctoral students:

Foundations 2: Modeling Intraindividual Variabilty and Change, 12 & 19 April
Foundations 2: Stochastic Models of Time-Dependent Cognitive Mechanisms,
30 April & 11 June
Foundations 2: Multinomial-Processing-Tree (MPT) Modeling: Basic Methods and Recent Advances, dates tba

Advanced topics in browser-based experimentation, 22 March – 25 March 2021 (3:30 p.m. – 5:30 p.m.) and 23 April 2021 (1 p.m. – 6 p.m.)

Multiverse Analysis: Taming Modelers’ Many Degrees of Freedom, 26 March (9 am – 5 pm) and 29 April 2021 (1:45 pm – 5 pm)

Advanced topics in R, 9 April 2021 (9 am – 5 pm)

Basic Concepts of Stochastic Processes, 15 &16 April 2021 (9 am – 5 pm)

Hands-on Open Science, 6 May 2021 (9 am – 5 pm)

Bridge sampling: An efficient method to approach inequality constrained hypotheses, 7 May 2021 (9 am – 5 pm)

Two-Process-Theories: An overview, 12 May 2021 (9 am – 5 pm)

IRT Modeling – Theory and Applications in R **, TBA May (9 am – 5 pm)

Multilevel Structural Equation Modeling, 14 June – 16 June 2021 (5 pm – 9 pm)

Modern R, 06 July 2021 (9 am – 5 pm)

 

Please register by sending an e-mail to Annette Förster.

 



Course Type: elective course

Course Number: MET/POL

Credits: 8

Prerequisites

Topics covered in introductory Game Theory class


Course Content

This course is a continuation of the intro into Game Theory and surveys key applications of game theory with a particular emphasis on the link of theories, methods and empirics. Emphasis will be placed on prominent applications of those concepts in political science, in both comparative and international politics. Topics covered include electoral competition, delegation, political agency, governmental veto players, authoritarian politics, manipulation, war and crisis bargaining. While the focus is on understanding applied work, previous training in game theory is required. Students will build upon their previous game theory training to become informed consumers of scholarship utilizing the methodology and begin to learn how to apply game-theoretic logic to their own work. The course is partly taught from lecture notes, at other times students present a research paper and stimulate discussion in class.

Course requirements & assessment

Class discussion, paper presentation, participation, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
01.03.21
14.06.21
Monday
15:30
17:00
Sowi Zoom 07


Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

lab.js is a simple, graphical tool to help you build studies for the web and the laboratory – in addition, it is free and open-source. Many standard tasks can be implemented in lab.js  using its graphical user interface. In addition, more complex tasks can be realized through the underlying programming language JavaScript. The goal of the workshop is to provide an introduction to both approaches. In doing so, the workshop involves both structured input from the instructor as well as a number of practical exercises so that participants can directly explore the features of lab.js. No prior knowledge of the software or JavaScript is required. As an assignment, participants will create their own experiment based on the requirements discussed in the workshop.

Course requirements & assessment

As an assignment (graded), participants will create their own experiment based on the requirements discussed in the workshop.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
16.04.21
23.04.21
Friday
10:15
15:15
Sowi Zoom 12
17.04.21
24.04.21
Saturday
10:15
17:00
Sowi Zoom 12

Lecturer(s)


Course Type: elective course

Course Number: MET/PSY

Credits: 4

Course Content

During recent years interventions using diary methods became increasingly popular within several fields of psychology, including health psychology and organizational psychology. These interventions use „intensive longitudinal designs“ to apply the treatment and to assess the data and build on daily-survey approaches that aim at „capturing life as it is lived” (Bolger, Davis, Rafaeli, 2003, p. 579). Frequent assessments typically implemented in daily-survey approaches allow for modeling change in affect, attitude, and behavior over time.
In this course we will discuss the nature of diary interventions, the research options they offer, as well as potential problems and challenges.

Literature (a more comprehensive list will be available in the first meeting)

Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54, 579-616.
Lischetzke, T., Reis, D., & Arndt, C. (2015). Data-analytic strategies for examining the effectiveness of daily interventions. Journal of Occupational and Organizational Psychology, 88, 587-622. doi:10.1111/joop.12104

Course requirements & assessment

Participation, presentation, term paper (graded)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
04.03.21
17.06.21
Thursday
17:15
18:45
Sowi Zoom 08


Course Type: elective course

Course Number: PSY

Course Content

The seminar takes place on Tuesdays from 5:15 p.m. to 6:45 p.m. Central European Time (CET), respectively Central European Summer Time (CEST) after 28 March 2021.

Full details

Confirmed speakers:

Norbert Schwarz (USC University of Southern California, CA, USA)

Klaus Oberauer (University of Zurich, Switzerland)

Anne Cleary (CSU Colorado State University, CO, USA)

Miri Besken (Bilkent University, Turkey)

Benjamin Scheibehenne (Karlsruhe Institute of Technology (KIT), Germany)

Zehra Peynircioğlu (The American University Washington DC, USA)

Gordon Pennycook (University of Regina, Canada)

Raoul Bell (Heinrich-Heine-Universität Düsseldorf, Germany)

Benjamin Hilbig (University of Landau, Germany)

Vanessa Loaiza (University of Essex, UK)

Josefa Pandeirada (University of Aveiro, Portugal)


Lecturer(s)


Course Type: elective course

Course Number: PSY

Credits: 4

Course Content

We invite CDSS doctoral candidates to discuss their research with experts in the field. The chair of Clinical Psychology and Biological Psychology and Psychotherapy pursues a wide range of topics and brings together a large spectrum of research approaches. We address open questions regarding each step of creative research and prolific publication of our scientific results. Each week we select one or two of our own projects for discussion.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
02.03.21
15.06.21
Tuesday
08:30
10:00
Sowi Zoom 09


Course Type: elective course

Course Number: RES

Credits: 5

Prerequisites

This course is exclusively geared towards students who are currently doctoral students at the GESS of the University of Mannheim. It is intended for beginning as well as advanced doctoral students. This course is an elective course and counts as a 'Bridge Course'. Maximum number of participants is 15. If the course is not fully booked, non-GESS students from Business, Economics, or the Social Sciences or from other related disciplines can enroll.


Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS. This year, the course will be given by one senior researchers from each center of the GESS, i.e., you will have the unique opportunity to receive truly interdisciplinary feedback on your work from three different angles.  

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by the instructors, each participant will shortly (max 5 min, 2-3 slides per person) present the core idea of an interdisciplinary paper published in a top journal in her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. Mini Research Day

The second component of the course is a ‘Mini-Research-Day’ which is intended to introduce the kind of topics you are working on to the other participants. You will give a presentation on a current working paper or research project of yours and you will discuss a paper/presentation from one of your fellow students from another field (10 min presentation, 5 min discussion, 10 min Q&A).

3. Science Speed Dating

The science speed dating event - organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a student from another field (preferably from our course).

4. Project Presentations & Writeups

This proposal will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in two weeks after the presentation.

Course requirements & assessment

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in the ‘Mini Research Day’. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant 10 days before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Course dates

  • March 11th, 2021, 12.30-3.30pm, Kick-Off Meeting
  • April 12th, 2021 - Deadline to send paper to discussant (and in cc: to gess@uni-  mannheim.de)
  • April 22th, 2021 – Mini Research Day (whole day symposium)
  • April 28th, time tba - Science Speed Dating Event
  • May 28th, 2021, Presentation of research proposal (half- to full day symposium)
  • June 13th, 2021 - Deadline to hand in interdisciplinary research proposal (to: gess@uni-mannheim.de)

Competences acquired

Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have received feedback from senior researchers from all three centers.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.