Doctoral theses supervised by professors in the department of Sociology will be discussed. Please check with individual chairs for dates and times.
Crafting Social Science Research, Literature Review
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. Only the first meeting will be held online, the remainder of the semester you'll meet in person.
Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.
Workshop | |||||||
further dates tbd | 13.02.24 | Tuesday | 10:15 – 11:45 | Zoom | Link | ||
Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.
The course will be taught by Prof. Marc Ratkovic, PhD
Course requirements & assessment
Active participation, term paper (graded)
Workshop | |||||||
13.02.24 – 28.05.24 | Tuesday | 08:30 – 10:00 | 211 in B6, 30–32 | ||||
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.
Dates tbd
Workshop | |||||||
13.02.24 – 28.05.24 | Tuesday | 17:15 – 18:45 | 209 in B6, 30–32 | ||||
CDSS doctoral students in political science and sociology can choose freely which weekly colloquium to attend. Colloquia must be attended regularly in year two and three of doctoral studies.
Please choose from
MZES Colloquium A “European Societies and their Integration”
MZES Colloquium B “European Political Systems and their Integration”
Please refer to the MZES web page for all further details. The talk announcements will be communicated via the CDSS mailing list as well.
Alternatively you can attend the Mannheim Research Colloquium on Survey Methods (MaRCS) or the MZES Social Science Data Lab, which will be announced through the Faculty of Social Sciences mailing list.
CSSR, Literature Review
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/
Course requirements & assessment
Term paper
Workshop | |||||||
15.02.24 – 23.05.24 | Thursday | 12:00 – 13:30 | B 317 in A5, 6 entrance B | Link | |||
Johannes Lattmann is the recipient of the 2023 CDSS Young Scholar Award, which he received for his project 'Next GESS – Career Talks for PhD and Master students with Industry, NGOs, and Policy Institutions'.
For this upcoming semester he organized the “Next GESS” Job Talk Series for doctoral students. Every Thursday, from 16.30 – 17.30 he invites a speaker to talk Online via Zoom about their job and career. The precise schedule can be found in the Syllabus which you can find in the appendix.
In the context of this series, he has invited speakers from a variety of companies and institutions including IBM, CEPS, OECD, UNESCO and many more. Through their experiences, this series aims to provide insights into exciting career trajectories. Eventually, this series should inform you about career opportunities and provide valuable insights about application processes and the day-to-day work life in different institutions.
Each session contains a 15–20 minutes long presentation by the speaker, introducing the respective job or institution. This is followed by a Q&A session in which you can ask questions.
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 24 July to 16 August. 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.
Knowledge of Multivariate Analysis
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).
Literature
Course requirements & assessment
Homework assignements, research paper (all graded)
Tutorial
The tutorial accompanies the course “Advanced Quantitative Methods” in Political Science.
Lecture | |||||||
14.02.24 – 29.05.24 | Wednesday | 08:30 – 10:00 | B 244 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
15.02.24 – 23.05.24 | Thursday | 10:15 – 11:45 | A 102 in B6, 23–25 | Link | |||
Selected topics relating to Generative AI in the social sciences are introduced in this seminar. Assigned readings and in-class activities will impart a deeper insight into the current status of research in this field, which is used to determine open questions and perspectives for further research.
Course taught by Prof. Joe Sakshaug.
Course requirements & assessment
For the examination, students write a term paper (5,000 words max.) where they either
1) carry out an empirical study in a focus area of social science research using Generative AI methods, OR
2) conduct a critical literature review of Generative AI used in the social sciences.
Upon completion of the module, students are able to:
• present their basic knowledge in Generative AI applied to social science research fields
• name the latest Generative AI developments in social science research
• describe their in-depth knowledge of empirical approaches to Generative AI in the social science research fields covered
• critically evaluate the empirical literature and applications of Generative AI in the social science research fields covered
Seminar | |||||||
16.02.24 – 31.05.24 | Friday | 08:30 – 10:00 | Online |
Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of comparative survey research. These surveys enable researchers to conduct cross-national/cross-cultural analysis, sometimes even across time. Yet, these important surveys come with their own challenge. The course covers the major steps of implementing and conducting a comparative survey and design decisions at each step. A special focus of the course will be on discussing sources of error that may be introduced by survey design decisions. For illustration purposes and exercise, the course will draw on examples and case studies from well-known cross-national surveys such as the European Social Survey (ESS), the European Values Study (EVS), the Generations and Gender Survey (GGS), the Programme for the International Assessment of Adult Competencies (PIAAC), and the World Values Survey (WVS).
Course requirements & assessment
Active participation, homework assignments/
Seminar | |||||||
16.02.24 – 31.05.24 | Friday | 10:15 – 11:45 | A 102 in B6, 23–25 | Link |
Some basic knowledge of statistical inference and R is required
Lecture
The course provides a broad overview of methods used in longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-section data, using measurements of the same individuals taken repeatedly through time can lead to better causal inferences in some cases, and can also give the possibility to learn more about the dynamics of individual behavior. The first objective of this course is to discuss the advantages of panel data, and the characteristics of the structure of panel data. Then, the course will give an overview of the main models (pooled OLS, fixed effects, random effects, first-differences) and provide the tools to choose betwen these models. The course will also discuss panel generalized linear models. Finally, an overview of event history analysis will be presented.
Tutorial
Using R, we apply methods of longitudinal data analysis (presented in the lecture “Longitudinal Data Analysis”) to real survey data.
The course will be taught by Dr. Danielle Martin
Course requirements & assessment
Lecture – Three quizzes (two must be a pass), regular attendance, written examination (graded, closed-book)
Tutorial -
Lecture | |||||||
12.02.24 – 27.05.24 | Monday | 10:15 – 11:45 | B 143 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
13.02.24 – 28.05.24 | Tuesday | 15:30 – 17:00 | B 143 in A5, 6 entrance B | Link | |||
The seminar gives an overview of
Regression and classification models are essential in many fields of psychological research as well as in clinical and epidemiological contexts. In this seminar, the models are introduced with their mathematical and statistical foundations, including model equations, methods of parameter estimation, and criteria of statistical inference. Statistical concepts and model applications are illustrated with simulations and through analyses of real data with R.
Literature
Dunn, P. K., & Smyth, G. K. (2018). Generalized linear models with examples in R. New York: Springer.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An intro¬duction to statistical learning with applications in R. New York: Springer.
Course requirements & assessment
Participation and written exam (graded)
Seminar | |||||||
not on 25 March | 12.02.24 – 27.05.24 | Monday | 10:15 – 11:45 | A 103 in B6, 23–25 | Link |
Please register for the SMiP course program via their online registration tool by 15 February.
This workshop provides an introduction to Item Response Theory (IRT) with basic and advanced models for dichotomous and polytomous items. The topics include the Rasch model and extensions with two, three and four item parameters for dichotomous items. Concerning polytomous items, we discuss the partial credit and rating scale model, generalized partial-credit model and graded response model for items with ordinal response format, and the nominal response model for items with categorical response format. In addition, multidimensional IRT models for response styles and IRTree models for multiple response processes are presented.
The IRT models are outlined with their formal model equations, theoretical assumptions and implications, estimation techniques, and statistical testing procedures. Applications to simulated and real data sets illustrate the use of IRT models for the analysis of individual differences in basic and applied research.
The workshop includes practical exercises of IRT modeling and analysis with current R packages. Basic knowledge and experience in R, including data management and use of R packages, are required for participation in this workshop.
The language of instruction is English. The course program includes online meetings, videos and analysis projects as homework.
Literature
Seminar | |||||||
16.02.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | Link | |||
15.03.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | ||||
26.04.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | ||||
24.05.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 |
The reading course is aimed at Ph.D. students in or beyond their second year to support them during their research phase. 1st year PhD students are welcomed to attend the class as well.
Recommended: Knowledge of basic statistics and prior experience with R or Stata is helpful, but not necessary.
This reading course provides a hands-on and paper-based approach to understanding and analyzing data. For many projects, collection of new data or experimental designs are the only way to answer a research question or to provide the decisive complementary evidence. Different ways to collect data can have important implications for model estimation and evaluation, parameter inference, and policy conclusions. Standard econometric methods start from assumptions about the sampling procedure and try to cope with the limitations of a given dataset. Instead, we start at the design stage and examine the interplay between sampling and experimental methods, statistical inference and estimation of causal effects. We will use the German Business Panel as point in case and implement cutting-edge methods to gain insights into the causal mechanisms behind reported outcomes. In each session, one of the participants will present a research paper, which we will discuss in light of concrete implementation at trial scale. Participants are encouraged to present research that is valuable for their own thesis or may be assigned to present a topic.
In addition to presenting a paper and participating in the discussion, students are expected to write a short technical report that summarizes the methods and implications in a way useful for peers who want to use the newly collected data or learn about experimental results.
The course is also part of the TRR 266 Accounting for Transparency
Learning outcomes:
The specific applications cover a broad set of skills with a focus on design of questionnaires and survey experiments, data analysis and quantitative methods, classification, inference, writing of own reports, and opportunities for own research.
TRR Members are welcome to join the course
Lecture | |||||||
Lecture | 13.02.24 – 28.05.24 | Tuesday | 10:15 – 11:45 | room O 048 | |||
Almost every doctoral dissertation is marked by difficult periods and times of frustration, which can also affect one´s mental health.
Not only aspects directly related to one's dissertation but also structural and/
The aim of this course is to get to know and discuss typical risk factors and challenging constellations doctoral students are likely to face during their dissertations. The course will consist of literature-informed/guided group discussions of several predefined topics addressing common difficulties during dissertation projects. During the first session(s), the group will decide the particular topics of interest for each of the sessions based on a brief literature discussion and their personal interests. Then, based on selected literature provided by the lecturer, the students will discuss these topics both from an academic standpoint and from their individual perspective/
The course will be taught by Dr. Matthias Volz
Course requirements & assessment
Students need to be willing to read articles, and discuss and articulate their own views on typical challenging situations during dissertation projects in guided group discussions.
Seminar | |||||||
bi-weekly | 20.02.24 – 19.03.24 | Tuesday | 10:15 – 11:45 | 209 in B6, 30–32 | |||
bi-weekly | 09.04.24 – 21.05.24 | Tuesday | 10:15 – 11:45 | 209 in B6, 30–32 |
Prerequisites: For each session, students need to have read the respective book in advance. (Detailed schedule will be provided in an introductory session.)
Form of Assessment: Essay 50 %, Class Participation 50 %
Friedman, M. (1963). Capitalism and Freedom. University of Chicago Press.
Deaton, A. (2023). Economics in America: An Immigrant Economist Explores the Land of Inequality. Princeton University Press.
Sandel, M. J. (2020). The Tyranny of Merit: What’s Become of the Common Good?. Penguin UK.
Bowles, S. (2016). The moral economy. Yale University Press.
Formal: Students need to be enrolled a PhD program at the GESS at the University of Mannheim, or the Master of Political Science.
Required: Willingness to read, discuss, challenge, engage and think for yourself is critical for this course.
We live in interesting times both, economically and politically. Many observers point to crises and uncertain developments in the economic and political world. Making sense of the nature of these challenges and pointing toward economic and political solutions for the future requires new perspectives. This is a course about the big and bold questions in economics and politics. How can or should economics and politics be organized to best serve society? What does it mean to put humans as they really are at the center of economic and political thinking? What role do morals and values, or dignity and respect, play for the way economics and politics work? What are the implications of digitalization for capitalism and freedom?
We will try to come to grips with these questions by reading and discussing four key books on various new perspectives at the intersection between economics and politics. The aim of this course is to go as deep as we can and to get as much out of an in-class discussion of the material as possible. Willingness to acquire and read the books is a must. If you are unsure about whether or not you would want to take on the commitment of reading four books in one semester then this course is probably not the right one for you.
Students need to be willing to read books, form their own opinions on them, and elaborate on and defend their own views in group discussions and a final essay.
We will meet for an introductory session on Monday 4.3. at 13.45–15.15 and then meet again for a total of seven Thursday and Wednesday sessions after the Easter break: 11.4., 25.4., 2.5., 8.5., 16.5., 23.5., and 29.5. at 8.30–11.45.
Learning outcomes: The aim of this course is to engage in intellectual dialogue, to develop a personal point of view on some of the central economic and political questions we face today, and to allow ourselves to think creatively, freely, and out of the box. After completing this course, students will have read important texts on new perspectives in economics and politics, they will have trained their ability to distill an own point of view from the writings of leading scientists, they will train their writing and discussion skills, and they will train to creatively apply what they have read in writing about the future of economics and politics in our society.
Lecture | |||||||
Introduction to the Course | 04.03.24 – 04.03.24 | Monday | 13:45 – 15:15 | L9, 1–2, Room 409 | |||
Lecture | 11.04.24 – 11.04.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 25.04.24 – 25.04.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 02.05.24 – 02.05.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 08.05.24 – 08.05.24 | Wednesday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 16.05.24 – 16.05.24 | Thursday | 08:30 – 11:45 | B6, 23–25, Room A301 | |||
Lecture | 23.05.24 – 23.05.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 29.05.24 – 29.05.24 | Wednesday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
What explains the rise of the Medici in 15th century Florence? Why did thousands of women join the guerilla war in 1980s El Salvador? What can online book co-purchases tell us about ideological differences between Republicans and Democrats in contemporary America? These are some of the questions we will grapple with as we explore how social scientists have applied network analysis to the study of politics.
The course is designed as a general introduction to social network analysis, but it focuses heavily on examples from political sociology (and adjacent fields) as one area in which network theories and methodologies have had a great influence. We will treat network analysis both as a theoretical approach that regards relations as the basic building blocks of social life, and as a methodological toolkit for visualizing and analyzing the structure of relations. Many of these methods involve the quantitative measurement of network structures (e.g., the degree to which networks are clustered) and different positions within the network (e.g., central vs. peripheral actors). The course is organized around a set of key concepts and theoretical insights in network analysis – such as weak ties, brokerage, and diffusion – which we will apply to a variety of substantive issues ranging from recruitment into social movements to the emergence of new political identities to the nature of political action.
The best way to learn about social networks is to work with them, which is why the class has a large practical component. After developing the theoretical foundations in class discussions, students will learn how to analyze networks in a series of practical assignments. The final project will give students an opportunity to follow their own curiosity and apply the analytical tools introduced in class to an empirical context of their choosing.
This course will be taught by Benjamin Rohr
Course requirements & assessment
Regular & active participation, formulation of questions/
Seminar | |||||||
12.02.24 – 27.05.24 | Monday | 13:45 – 15:15 | B 143 in A5, 6 entrance B |
An increasing base of literature shows ‘disappointing poverty trends’ both in the global North and the global South. Inequality in many societies is on the rise: gains of globalization have been concentrated with a small elite while incomes and wealth of the rest have stagnated or declined. At the same time, school systems and welfare provisions have expanded, aiming at equalizing opportunities. How to explain this paradox of increasing opportunities and disappointing poverty and inequality trends? This seminar examines aspects of poverty and inequality from a sociological perspective, with insights from economics and public policy. It covers contexts of all levels of development, including high- and low- income countries. In the first part, we discuss the definitions and measurements of poverty and inequality, how they vary across countries and change over time, and critically assess how such variation may create identification issues and affect policy responses. In the second part, we review empirical research findings in sociology and economics regarding poverty and inequality in different contexts and globally. We take a closer look at different cross-sectional and longitudinal research designs that consider poverty and inequality as static and dynamic phenomena, and look at different population subgroups: children, workforce, and the elderly. In the third part, we investigate how policy interventions affect poverty and inequality. We examine the effectiveness of cash transfers, employment, care services and taxes as policy responses, and discuss issues related to policy design such as conditionality, targeting, social investment provisions, and their redistributive implications.
The course will be taught by Prof. Ilze Plavgo
Course requirements & assessment
1. Students are expected to read the assigned readings for each week before coming to class, and actively engage in discussions during the seminar sessions.
2. One oral presentation of one of the assigned readings of approx. 8 minutes with 4–5 PPT slides. PPT slides to be uploaded on the ILIAS one day before class.
3. Two response papers of 300–400 words each: short reflections about theoretical arguments or questions provoked by the assigned readings of two sessions of choice, uploaded 1 day before class.
Written term paper (graded) on a topic related to the seminar, in English, composed of two parts with a total of 5,000 words:
1) Term paper outline (500 words) a week before the last session (Friday 17 May noon)
2) Term paper (4,500 words, excl. literature, appendix), a month after the last session (1st July noon)
Seminar | |||||||
12.02.24 – 27.05.24 | Monday | 13:45 – 15:15 | B 318 in A5, 6 entrance B | Link |
“Like father, like son!” “Someone's a chip off the old block!” “To follow in his father's footsteps!” There is a variety of popular proverbs describing the same (sociological) fact: Social origin, i.e. the class or income position of parents, has a large effect on the future life-chances (class position, income) of their children. For example, a child from a working-class background has considerably lower prospects of achieving a position as a professional compared to a child whose parents work as professionals. And the same is true vice versa. Asking about social mobility or immobility across generations is one of the classic questions in sociology. The seminar will offer a comprehensive view on concepts of intergenerational (and intragenerational) social mobility, on theoretical approaches to explain social mobility, on quantitative methodological approaches and on empirical results regarding the amount of social mobility in Europe. Students are expected to read and discuss the most prominent articles in the field, including technical/
Course requirements & assessment
Regular small assignments (developing research questions based on the readings); compulsory attendance; participating in active discussion.
Written term paper (graded, max. 5000 words), deadline: July 31, 2024
Seminar | |||||||
21.02.24 | Wednesday | 08:30 – 11:45 | C116 in A5, 6 entrance C | Link | |||
28.02.24 | Wednesday | 08:30 – 11:45 | C116 in A5, 6 entrance C | ||||
20.03.24 | Wednesday | 08:30 – 11:45 | C116 in A5, 6 entrance C | ||||
bi-weekly | 10.04.24 – 08.05.24 | Wednesday | 08:30 – 11:45 | C116 in A5, 6 entrance C | |||
15.05.24 | Wednesday | 08:30 – 11:45 | C116 in A5, 6 entrance C |
Doctoral theses supervised by professors in the department of Political Science will be discussed.
Please check with individual chairs for dates and times.
Crafting Social Science Research, Literature Review
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. Only the first meeting will be held online, the remainder of the semester you'll meet in person.
Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.
Workshop | |||||||
further dates tbd | 13.02.24 | Tuesday | 10:15 – 11:45 | Zoom | Link | ||
Knowledge of Multivariate Analysis
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).
Literature
Course requirements & assessment
Homework assignements, research paper (all graded)
Tutorial
The tutorial accompanies the course “Advanced Quantitative Methods” in Political Science.
Lecture | |||||||
14.02.24 – 29.05.24 | Wednesday | 08:30 – 10:00 | B 244 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
15.02.24 – 23.05.24 | Thursday | 10:15 – 11:45 | A 102 in B6, 23–25 | Link | |||
Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.
The course will be taught by Prof. Marc Ratkovic, PhD
Course requirements & assessment
Active participation, term paper (graded)
Workshop | |||||||
13.02.24 – 28.05.24 | Tuesday | 08:30 – 10:00 | 211 in B6, 30–32 | ||||
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) 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.
Workshop | |||||||
12.02.24 – 27.05.24 | Monday | 15:30 – 17:00 | A 102 in B6, 23–25 | ||||
CDSS doctoral students in political science and sociology can choose freely which weekly colloquium to attend. Colloquia must be attended regularly in year two and three of doctoral studies.
Please choose from
MZES Colloquium A “European Societies and their Integration”
MZES Colloquium B “European Political Systems and their Integration”
Please refer to the MZES web page for all further details. The talk announcements will be communicated via the CDSS mailing list as well.
Alternatively you can attend the Mannheim Research Colloquium on Survey Methods (MaRCS) or the MZES Social Science Data Lab, which will be announced through the Faculty of Social Sciences mailing list.
CSSR, Literature Review
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/
Course requirements & assessment
Term paper
Workshop | |||||||
15.02.24 – 23.05.24 | Thursday | 12:00 – 13:30 | B 317 in A5, 6 entrance B | Link | |||
Johannes Lattmann is the recipient of the 2023 CDSS Young Scholar Award, which he received for his project 'Next GESS – Career Talks for PhD and Master students with Industry, NGOs, and Policy Institutions'.
For this upcoming semester he organized the “Next GESS” Job Talk Series for doctoral students. Every Thursday, from 16.30 – 17.30 he invites a speaker to talk Online via Zoom about their job and career. The precise schedule can be found in the Syllabus which you can find in the appendix.
In the context of this series, he has invited speakers from a variety of companies and institutions including IBM, CEPS, OECD, UNESCO and many more. Through their experiences, this series aims to provide insights into exciting career trajectories. Eventually, this series should inform you about career opportunities and provide valuable insights about application processes and the day-to-day work life in different institutions.
Each session contains a 15–20 minutes long presentation by the speaker, introducing the respective job or institution. This is followed by a Q&A session in which you can ask questions.
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 24 July to 16 August. 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.
Selected topics relating to Generative AI in the social sciences are introduced in this seminar. Assigned readings and in-class activities will impart a deeper insight into the current status of research in this field, which is used to determine open questions and perspectives for further research.
Course taught by Prof. Joe Sakshaug.
Course requirements & assessment
For the examination, students write a term paper (5,000 words max.) where they either
1) carry out an empirical study in a focus area of social science research using Generative AI methods, OR
2) conduct a critical literature review of Generative AI used in the social sciences.
Upon completion of the module, students are able to:
• present their basic knowledge in Generative AI applied to social science research fields
• name the latest Generative AI developments in social science research
• describe their in-depth knowledge of empirical approaches to Generative AI in the social science research fields covered
• critically evaluate the empirical literature and applications of Generative AI in the social science research fields covered
Seminar | |||||||
16.02.24 – 31.05.24 | Friday | 08:30 – 10:00 | Online |
Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of comparative survey research. These surveys enable researchers to conduct cross-national/cross-cultural analysis, sometimes even across time. Yet, these important surveys come with their own challenge. The course covers the major steps of implementing and conducting a comparative survey and design decisions at each step. A special focus of the course will be on discussing sources of error that may be introduced by survey design decisions. For illustration purposes and exercise, the course will draw on examples and case studies from well-known cross-national surveys such as the European Social Survey (ESS), the European Values Study (EVS), the Generations and Gender Survey (GGS), the Programme for the International Assessment of Adult Competencies (PIAAC), and the World Values Survey (WVS).
Course requirements & assessment
Active participation, homework assignments/
Seminar | |||||||
16.02.24 – 31.05.24 | Friday | 10:15 – 11:45 | A 102 in B6, 23–25 | Link |
Some basic knowledge of statistical inference and R is required
Lecture
The course provides a broad overview of methods used in longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-section data, using measurements of the same individuals taken repeatedly through time can lead to better causal inferences in some cases, and can also give the possibility to learn more about the dynamics of individual behavior. The first objective of this course is to discuss the advantages of panel data, and the characteristics of the structure of panel data. Then, the course will give an overview of the main models (pooled OLS, fixed effects, random effects, first-differences) and provide the tools to choose betwen these models. The course will also discuss panel generalized linear models. Finally, an overview of event history analysis will be presented.
Tutorial
Using R, we apply methods of longitudinal data analysis (presented in the lecture “Longitudinal Data Analysis”) to real survey data.
The course will be taught by Dr. Danielle Martin
Course requirements & assessment
Lecture – Three quizzes (two must be a pass), regular attendance, written examination (graded, closed-book)
Tutorial -
Lecture | |||||||
12.02.24 – 27.05.24 | Monday | 10:15 – 11:45 | B 143 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
13.02.24 – 28.05.24 | Tuesday | 15:30 – 17:00 | B 143 in A5, 6 entrance B | Link | |||
The seminar gives an overview of
Regression and classification models are essential in many fields of psychological research as well as in clinical and epidemiological contexts. In this seminar, the models are introduced with their mathematical and statistical foundations, including model equations, methods of parameter estimation, and criteria of statistical inference. Statistical concepts and model applications are illustrated with simulations and through analyses of real data with R.
Literature
Dunn, P. K., & Smyth, G. K. (2018). Generalized linear models with examples in R. New York: Springer.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An intro¬duction to statistical learning with applications in R. New York: Springer.
Course requirements & assessment
Participation and written exam (graded)
Seminar | |||||||
not on 25 March | 12.02.24 – 27.05.24 | Monday | 10:15 – 11:45 | A 103 in B6, 23–25 | Link |
Please register for the SMiP course program via their online registration tool by 15 February.
This workshop provides an introduction to Item Response Theory (IRT) with basic and advanced models for dichotomous and polytomous items. The topics include the Rasch model and extensions with two, three and four item parameters for dichotomous items. Concerning polytomous items, we discuss the partial credit and rating scale model, generalized partial-credit model and graded response model for items with ordinal response format, and the nominal response model for items with categorical response format. In addition, multidimensional IRT models for response styles and IRTree models for multiple response processes are presented.
The IRT models are outlined with their formal model equations, theoretical assumptions and implications, estimation techniques, and statistical testing procedures. Applications to simulated and real data sets illustrate the use of IRT models for the analysis of individual differences in basic and applied research.
The workshop includes practical exercises of IRT modeling and analysis with current R packages. Basic knowledge and experience in R, including data management and use of R packages, are required for participation in this workshop.
The language of instruction is English. The course program includes online meetings, videos and analysis projects as homework.
Literature
Seminar | |||||||
16.02.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | Link | |||
15.03.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | ||||
26.04.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | ||||
24.05.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 |
The reading course is aimed at Ph.D. students in or beyond their second year to support them during their research phase. 1st year PhD students are welcomed to attend the class as well.
Recommended: Knowledge of basic statistics and prior experience with R or Stata is helpful, but not necessary.
This reading course provides a hands-on and paper-based approach to understanding and analyzing data. For many projects, collection of new data or experimental designs are the only way to answer a research question or to provide the decisive complementary evidence. Different ways to collect data can have important implications for model estimation and evaluation, parameter inference, and policy conclusions. Standard econometric methods start from assumptions about the sampling procedure and try to cope with the limitations of a given dataset. Instead, we start at the design stage and examine the interplay between sampling and experimental methods, statistical inference and estimation of causal effects. We will use the German Business Panel as point in case and implement cutting-edge methods to gain insights into the causal mechanisms behind reported outcomes. In each session, one of the participants will present a research paper, which we will discuss in light of concrete implementation at trial scale. Participants are encouraged to present research that is valuable for their own thesis or may be assigned to present a topic.
In addition to presenting a paper and participating in the discussion, students are expected to write a short technical report that summarizes the methods and implications in a way useful for peers who want to use the newly collected data or learn about experimental results.
The course is also part of the TRR 266 Accounting for Transparency
Learning outcomes:
The specific applications cover a broad set of skills with a focus on design of questionnaires and survey experiments, data analysis and quantitative methods, classification, inference, writing of own reports, and opportunities for own research.
TRR Members are welcome to join the course
Lecture | |||||||
Lecture | 13.02.24 – 28.05.24 | Tuesday | 10:15 – 11:45 | room O 048 | |||
Natural experiments have become increasingly popular in political science research. By leveraging the “as-if” random assignment to units to real-word interventions or treatments, such methods allow scholars to draw causal inferences from observational data. Yet finding good natural experiments is as much of an art as a science. To that end, this course aims to help students recognize and discover opportunities for natural experimental research by surveying a broad range of empirical applications. Students should leave the course with both (i) a repertoire of potential natural experimental designs and (ii) the skills to evaluate the promises and pitfalls of such research.
The course will be taught by Nan Zhang, PhD
Course requirements & assessment
Term paper (graded)
Seminar | |||||||
14.02.24 – 29.05.24 | Wednesday | 10:15 – 11:45 | tbc | Link |
Comparison is essential to research in comparative political behavior. At the same time, it raises multiple conceptual and measurement issues. Questions include what is ‘similar’, what is ‘different’, and what is incommensurable, and how can we figure out whether measures are equivalent or not. In this seminar, we will address conceptual and methodological issues in measurement and comparison in comparative political research.
Course requirements & assessment
Students will review empirical studies in the field and prepare research papers in which they analyze specific questions using available data sets., term paper (graded)
Seminar | |||||||
13.02.24 – 28.05.24 | Tuesday | 12:00 – 13:30 | B 318 in A5, 6 entrance B | Link |
In this course students are required to prepare the scholarly on different models of governance and to do empirical analyses for studying affective polarization of democracy and its challenges by technocracism and populism. Ideally, students know about the state of the art and can command statistical models using R. We will also distinguish between associational and causal research designs, assumptions on the data generation process, theoretical and statistical identification.
Literature
Course requirements and assessment
Preparation of sessions, presentation of 2 studies, active and regular participation is recommended, term paper (12–15 pages, graded)
Seminar | |||||||
15.02.24 – 23.05.24 | Thursday | 12:00 – 13:30 | B318 in A5, 6 entrance B | Link |
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
Regular participation is recommended, mandatory reading, term paper (graded)
Lecture | |||||||
12.02.24 – 27.05.24 | Monday | 10:15 – 11:45 | B 244 in A5, 6 entrance B | Link | |||
The security of individuals and states depends profoundly on international politics. Beyond the realm of security, structures and actors of “global governance” have been proliferating for many years. They influence crucial public policies in diverse ways. This lecture surveys academic debates on key topics of international politics, including: the sources of war, peace, and terrorism, the emergence and operation of international organizations and transnational civil society, and the making of key international policy outcomes including respect for human rights and climate policies.
Course requirements & assessment
Written exam (graded)
Lecture | |||||||
12.02.24 – 27.05.24 | Monday | 13:45 – 15:15 | B 244 in A5, 6 entrance B | Link | |||
This lecture gives an overview of selected theoretical concepts and the main research findings in the field of Comparative Government, specifically focusing on the role of political institutions and their impact for political decision-making at all stages in the political process. The course introduces a number of core themes in the comparative study of political institutions, such as electoral institutions and their effects on turnout, voting behaviour and party strategies. In addition, the lecture focuses on the impact of different institutional designs on patterns of party competition, government formation and coalition governance. In a third step, we discuss the effects of political institutions and of personal characteristics of legislators on various aspects of decision-making within parliaments and governments.
The course will be taught by Or Tuttnauer, PhD
Course requirements & assessment
Lecture of recommended texts, written exam (graded)
Lecture | |||||||
13.02.24 – 28.05.24 | Tuesday | 10:15 – 11:45 | C217 in A5, 6 entrance C | Link | |||
In this seminar, we study the political economy of international organizations (IOs) with quantitative methods for causal inference. Our focus will be on the major IOs such as the United Nations (UN), the World Bank, the International Monetary Fund (IMF), and the European Union (EU). We will examine and discuss research on how these organizations operate, how they make decisions, and how they affect political and economic outcomes in their member states. Methodologically, the course will place an emphasis on literature that applies quantitative methods of causal inference and students will learn how these methods are applied in research practice. We will also discuss the political implications of the empirical findings for the future of global economic governance.In this seminar, we study the political economy of international organizations (IOs) with quantitative methods for causal inference. Our focus will be on the major IOs such as the United Nations (UN), the World Bank, the International Monetary Fund (IMF), and the European Union (EU). We will examine and discuss research on how these organizations operate, how they make decisions, and how they affect political and economic outcomes in their member states. Methodologically, the course will place an emphasis on literature that applies quantitative methods of causal inference and students will learn how these methods are applied in research practice. We will also discuss the political implications of the empirical findings for the future of global economic governance.In this seminar, we study the political economy of international organizations (IOs) with quantitative methods for causal inference. Our focus will be on the major IOs such as the United Nations (UN), the World Bank, the International Monetary Fund (IMF), and the European Union (EU). We will examine and discuss research on how these organizations operate, how they make decisions, and how they affect political and economic outcomes in their member states. Methodologically, the course will place an emphasis on literature that applies quantitative methods of causal inference and students will learn how these methods are applied in research practice. We will also discuss the political implications of the empirical findings for the future of global economic governance.
Course requirements & assessment
Active participation, term paper (graded)
Seminar | |||||||
13.02.24 – 28.05.24 | Tuesday | 13:45 – 15:15 | B 317 in A5, 6 entrance B | Link |
Almost every doctoral dissertation is marked by difficult periods and times of frustration, which can also affect one´s mental health.
Not only aspects directly related to one's dissertation but also structural and/
The aim of this course is to get to know and discuss typical risk factors and challenging constellations doctoral students are likely to face during their dissertations. The course will consist of literature-informed/guided group discussions of several predefined topics addressing common difficulties during dissertation projects. During the first session(s), the group will decide the particular topics of interest for each of the sessions based on a brief literature discussion and their personal interests. Then, based on selected literature provided by the lecturer, the students will discuss these topics both from an academic standpoint and from their individual perspective/
The course will be taught by Dr. Matthias Volz
Course requirements & assessment
Students need to be willing to read articles, and discuss and articulate their own views on typical challenging situations during dissertation projects in guided group discussions.
Seminar | |||||||
bi-weekly | 20.02.24 – 19.03.24 | Tuesday | 10:15 – 11:45 | 209 in B6, 30–32 | |||
bi-weekly | 09.04.24 – 21.05.24 | Tuesday | 10:15 – 11:45 | 209 in B6, 30–32 |
Prerequisites: For each session, students need to have read the respective book in advance. (Detailed schedule will be provided in an introductory session.)
Form of Assessment: Essay 50 %, Class Participation 50 %
Friedman, M. (1963). Capitalism and Freedom. University of Chicago Press.
Deaton, A. (2023). Economics in America: An Immigrant Economist Explores the Land of Inequality. Princeton University Press.
Sandel, M. J. (2020). The Tyranny of Merit: What’s Become of the Common Good?. Penguin UK.
Bowles, S. (2016). The moral economy. Yale University Press.
Formal: Students need to be enrolled a PhD program at the GESS at the University of Mannheim, or the Master of Political Science.
Required: Willingness to read, discuss, challenge, engage and think for yourself is critical for this course.
We live in interesting times both, economically and politically. Many observers point to crises and uncertain developments in the economic and political world. Making sense of the nature of these challenges and pointing toward economic and political solutions for the future requires new perspectives. This is a course about the big and bold questions in economics and politics. How can or should economics and politics be organized to best serve society? What does it mean to put humans as they really are at the center of economic and political thinking? What role do morals and values, or dignity and respect, play for the way economics and politics work? What are the implications of digitalization for capitalism and freedom?
We will try to come to grips with these questions by reading and discussing four key books on various new perspectives at the intersection between economics and politics. The aim of this course is to go as deep as we can and to get as much out of an in-class discussion of the material as possible. Willingness to acquire and read the books is a must. If you are unsure about whether or not you would want to take on the commitment of reading four books in one semester then this course is probably not the right one for you.
Students need to be willing to read books, form their own opinions on them, and elaborate on and defend their own views in group discussions and a final essay.
We will meet for an introductory session on Monday 4.3. at 13.45–15.15 and then meet again for a total of seven Thursday and Wednesday sessions after the Easter break: 11.4., 25.4., 2.5., 8.5., 16.5., 23.5., and 29.5. at 8.30–11.45.
Learning outcomes: The aim of this course is to engage in intellectual dialogue, to develop a personal point of view on some of the central economic and political questions we face today, and to allow ourselves to think creatively, freely, and out of the box. After completing this course, students will have read important texts on new perspectives in economics and politics, they will have trained their ability to distill an own point of view from the writings of leading scientists, they will train their writing and discussion skills, and they will train to creatively apply what they have read in writing about the future of economics and politics in our society.
Lecture | |||||||
Introduction to the Course | 04.03.24 – 04.03.24 | Monday | 13:45 – 15:15 | L9, 1–2, Room 409 | |||
Lecture | 11.04.24 – 11.04.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 25.04.24 – 25.04.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 02.05.24 – 02.05.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 08.05.24 – 08.05.24 | Wednesday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 16.05.24 – 16.05.24 | Thursday | 08:30 – 11:45 | B6, 23–25, Room A301 | |||
Lecture | 23.05.24 – 23.05.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 29.05.24 – 29.05.24 | Wednesday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Crafting Social Science Research, Literature Review
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. Only the first meeting will be held online, the remainder of the semester you'll meet in person.
Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.
Workshop | |||||||
further dates tbd | 13.02.24 | Tuesday | 10:15 – 11:45 | Zoom | Link | ||
Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.
The course will be taught by Prof. Marc Ratkovic, PhD
Course requirements & assessment
Active participation, term paper (graded)
Workshop | |||||||
13.02.24 – 28.05.24 | Tuesday | 08:30 – 10:00 | 211 in B6, 30–32 | ||||
TCBI, CSSR, Dissertation Proposal
Please check with individual chairs in the Psychology department for dates and times of research colloquia.
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 Psychology: Research projects 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.
Literature: References will be given during the course.
The workshop will be hosted by Prof. Arndt Bröder & Dr. Meike Kroneisen
Talk schedule
Improvement in research skills and communication of research results.
Workshop | |||||||
12.02.24 – 27.05.24 | Monday | 15:30 – 17:00 | C 217 in A5, 6 entrance C | ||||
CSSR, Literature Review
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/
Course requirements & assessment
Term paper
Workshop | |||||||
15.02.24 – 23.05.24 | Thursday | 12:00 – 13:30 | B 317 in A5, 6 entrance B | Link | |||
Johannes Lattmann is the recipient of the 2023 CDSS Young Scholar Award, which he received for his project 'Next GESS – Career Talks for PhD and Master students with Industry, NGOs, and Policy Institutions'.
For this upcoming semester he organized the “Next GESS” Job Talk Series for doctoral students. Every Thursday, from 16.30 – 17.30 he invites a speaker to talk Online via Zoom about their job and career. The precise schedule can be found in the Syllabus which you can find in the appendix.
In the context of this series, he has invited speakers from a variety of companies and institutions including IBM, CEPS, OECD, UNESCO and many more. Through their experiences, this series aims to provide insights into exciting career trajectories. Eventually, this series should inform you about career opportunities and provide valuable insights about application processes and the day-to-day work life in different institutions.
Each session contains a 15–20 minutes long presentation by the speaker, introducing the respective job or institution. This is followed by a Q&A session in which you can ask questions.
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 24 July to 16 August. 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.
Knowledge of Multivariate Analysis
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).
Literature
Course requirements & assessment
Homework assignements, research paper (all graded)
Tutorial
The tutorial accompanies the course “Advanced Quantitative Methods” in Political Science.
Lecture | |||||||
14.02.24 – 29.05.24 | Wednesday | 08:30 – 10:00 | B 244 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
15.02.24 – 23.05.24 | Thursday | 10:15 – 11:45 | A 102 in B6, 23–25 | Link | |||
Selected topics relating to Generative AI in the social sciences are introduced in this seminar. Assigned readings and in-class activities will impart a deeper insight into the current status of research in this field, which is used to determine open questions and perspectives for further research.
Course taught by Prof. Joe Sakshaug.
Course requirements & assessment
For the examination, students write a term paper (5,000 words max.) where they either
1) carry out an empirical study in a focus area of social science research using Generative AI methods, OR
2) conduct a critical literature review of Generative AI used in the social sciences.
Upon completion of the module, students are able to:
• present their basic knowledge in Generative AI applied to social science research fields
• name the latest Generative AI developments in social science research
• describe their in-depth knowledge of empirical approaches to Generative AI in the social science research fields covered
• critically evaluate the empirical literature and applications of Generative AI in the social science research fields covered
Seminar | |||||||
16.02.24 – 31.05.24 | Friday | 08:30 – 10:00 | Online |
Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of comparative survey research. These surveys enable researchers to conduct cross-national/cross-cultural analysis, sometimes even across time. Yet, these important surveys come with their own challenge. The course covers the major steps of implementing and conducting a comparative survey and design decisions at each step. A special focus of the course will be on discussing sources of error that may be introduced by survey design decisions. For illustration purposes and exercise, the course will draw on examples and case studies from well-known cross-national surveys such as the European Social Survey (ESS), the European Values Study (EVS), the Generations and Gender Survey (GGS), the Programme for the International Assessment of Adult Competencies (PIAAC), and the World Values Survey (WVS).
Course requirements & assessment
Active participation, homework assignments/
Seminar | |||||||
16.02.24 – 31.05.24 | Friday | 10:15 – 11:45 | A 102 in B6, 23–25 | Link |
Some basic knowledge of statistical inference and R is required
Lecture
The course provides a broad overview of methods used in longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-section data, using measurements of the same individuals taken repeatedly through time can lead to better causal inferences in some cases, and can also give the possibility to learn more about the dynamics of individual behavior. The first objective of this course is to discuss the advantages of panel data, and the characteristics of the structure of panel data. Then, the course will give an overview of the main models (pooled OLS, fixed effects, random effects, first-differences) and provide the tools to choose betwen these models. The course will also discuss panel generalized linear models. Finally, an overview of event history analysis will be presented.
Tutorial
Using R, we apply methods of longitudinal data analysis (presented in the lecture “Longitudinal Data Analysis”) to real survey data.
The course will be taught by Dr. Danielle Martin
Course requirements & assessment
Lecture – Three quizzes (two must be a pass), regular attendance, written examination (graded, closed-book)
Tutorial -
Lecture | |||||||
12.02.24 – 27.05.24 | Monday | 10:15 – 11:45 | B 143 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
13.02.24 – 28.05.24 | Tuesday | 15:30 – 17:00 | B 143 in A5, 6 entrance B | Link | |||
The seminar gives an overview of
Regression and classification models are essential in many fields of psychological research as well as in clinical and epidemiological contexts. In this seminar, the models are introduced with their mathematical and statistical foundations, including model equations, methods of parameter estimation, and criteria of statistical inference. Statistical concepts and model applications are illustrated with simulations and through analyses of real data with R.
Literature
Dunn, P. K., & Smyth, G. K. (2018). Generalized linear models with examples in R. New York: Springer.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An intro¬duction to statistical learning with applications in R. New York: Springer.
Course requirements & assessment
Participation and written exam (graded)
Seminar | |||||||
not on 25 March | 12.02.24 – 27.05.24 | Monday | 10:15 – 11:45 | A 103 in B6, 23–25 | Link |
Please register for the SMiP course program via their online registration tool by 15 February.
This workshop provides an introduction to Item Response Theory (IRT) with basic and advanced models for dichotomous and polytomous items. The topics include the Rasch model and extensions with two, three and four item parameters for dichotomous items. Concerning polytomous items, we discuss the partial credit and rating scale model, generalized partial-credit model and graded response model for items with ordinal response format, and the nominal response model for items with categorical response format. In addition, multidimensional IRT models for response styles and IRTree models for multiple response processes are presented.
The IRT models are outlined with their formal model equations, theoretical assumptions and implications, estimation techniques, and statistical testing procedures. Applications to simulated and real data sets illustrate the use of IRT models for the analysis of individual differences in basic and applied research.
The workshop includes practical exercises of IRT modeling and analysis with current R packages. Basic knowledge and experience in R, including data management and use of R packages, are required for participation in this workshop.
The language of instruction is English. The course program includes online meetings, videos and analysis projects as homework.
Literature
Seminar | |||||||
16.02.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | Link | |||
15.03.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | ||||
26.04.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 | ||||
24.05.24 | Friday | 10:15 – 11:45 | 108 CIP Pool in B6, 30–32 |
The reading course is aimed at Ph.D. students in or beyond their second year to support them during their research phase. 1st year PhD students are welcomed to attend the class as well.
Recommended: Knowledge of basic statistics and prior experience with R or Stata is helpful, but not necessary.
This reading course provides a hands-on and paper-based approach to understanding and analyzing data. For many projects, collection of new data or experimental designs are the only way to answer a research question or to provide the decisive complementary evidence. Different ways to collect data can have important implications for model estimation and evaluation, parameter inference, and policy conclusions. Standard econometric methods start from assumptions about the sampling procedure and try to cope with the limitations of a given dataset. Instead, we start at the design stage and examine the interplay between sampling and experimental methods, statistical inference and estimation of causal effects. We will use the German Business Panel as point in case and implement cutting-edge methods to gain insights into the causal mechanisms behind reported outcomes. In each session, one of the participants will present a research paper, which we will discuss in light of concrete implementation at trial scale. Participants are encouraged to present research that is valuable for their own thesis or may be assigned to present a topic.
In addition to presenting a paper and participating in the discussion, students are expected to write a short technical report that summarizes the methods and implications in a way useful for peers who want to use the newly collected data or learn about experimental results.
The course is also part of the TRR 266 Accounting for Transparency
Learning outcomes:
The specific applications cover a broad set of skills with a focus on design of questionnaires and survey experiments, data analysis and quantitative methods, classification, inference, writing of own reports, and opportunities for own research.
TRR Members are welcome to join the course
Lecture | |||||||
Lecture | 13.02.24 – 28.05.24 | Tuesday | 10:15 – 11:45 | room O 048 | |||
While culture is often seen as a hallmark of humanity, an evolutionary perspective challenges this view by proposing continuity in behavioral traits across species. According to this view, culture and its constituting elements exhibit variations in degree rather than kind.
Overall, the goal of this course is to understand how and why individuals (humans and nonhumans) learn in a social context, an essential component of culture. By adopting a (cross-species) comparative perspective, the course covers the mechanisms and functions of social learning, as well as its driving factors, including psychological aspects (cognitive and non-cognitive), and environmental determinants (physical and social), providing a deeper understanding of the evolutionary links that underlie cultural behaviors.
The course will be taught by Camilla Cenni, PhD
Course requirements & assessment
Active participation, homework, in-class presentation, term paper (graded)
Seminar | |||||||
13.02.24 – 28.05.24 | Tuesday | 10:15 – 11:45 | B 143 in A5, 6 entrance B | Link |
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.
Seminar | |||||||
13.02.24 – 28.05.24 | Tuesday | 12:00 – 13:30 | 016–017 in L13, 15–17 |
Almost every doctoral dissertation is marked by difficult periods and times of frustration, which can also affect one´s mental health.
Not only aspects directly related to one's dissertation but also structural and/
The aim of this course is to get to know and discuss typical risk factors and challenging constellations doctoral students are likely to face during their dissertations. The course will consist of literature-informed/guided group discussions of several predefined topics addressing common difficulties during dissertation projects. During the first session(s), the group will decide the particular topics of interest for each of the sessions based on a brief literature discussion and their personal interests. Then, based on selected literature provided by the lecturer, the students will discuss these topics both from an academic standpoint and from their individual perspective/
The course will be taught by Dr. Matthias Volz
Course requirements & assessment
Students need to be willing to read articles, and discuss and articulate their own views on typical challenging situations during dissertation projects in guided group discussions.
Seminar | |||||||
bi-weekly | 20.02.24 – 19.03.24 | Tuesday | 10:15 – 11:45 | 209 in B6, 30–32 | |||
bi-weekly | 09.04.24 – 21.05.24 | Tuesday | 10:15 – 11:45 | 209 in B6, 30–32 |
Prerequisites: For each session, students need to have read the respective book in advance. (Detailed schedule will be provided in an introductory session.)
Form of Assessment: Essay 50 %, Class Participation 50 %
Friedman, M. (1963). Capitalism and Freedom. University of Chicago Press.
Deaton, A. (2023). Economics in America: An Immigrant Economist Explores the Land of Inequality. Princeton University Press.
Sandel, M. J. (2020). The Tyranny of Merit: What’s Become of the Common Good?. Penguin UK.
Bowles, S. (2016). The moral economy. Yale University Press.
Formal: Students need to be enrolled a PhD program at the GESS at the University of Mannheim, or the Master of Political Science.
Required: Willingness to read, discuss, challenge, engage and think for yourself is critical for this course.
We live in interesting times both, economically and politically. Many observers point to crises and uncertain developments in the economic and political world. Making sense of the nature of these challenges and pointing toward economic and political solutions for the future requires new perspectives. This is a course about the big and bold questions in economics and politics. How can or should economics and politics be organized to best serve society? What does it mean to put humans as they really are at the center of economic and political thinking? What role do morals and values, or dignity and respect, play for the way economics and politics work? What are the implications of digitalization for capitalism and freedom?
We will try to come to grips with these questions by reading and discussing four key books on various new perspectives at the intersection between economics and politics. The aim of this course is to go as deep as we can and to get as much out of an in-class discussion of the material as possible. Willingness to acquire and read the books is a must. If you are unsure about whether or not you would want to take on the commitment of reading four books in one semester then this course is probably not the right one for you.
Students need to be willing to read books, form their own opinions on them, and elaborate on and defend their own views in group discussions and a final essay.
We will meet for an introductory session on Monday 4.3. at 13.45–15.15 and then meet again for a total of seven Thursday and Wednesday sessions after the Easter break: 11.4., 25.4., 2.5., 8.5., 16.5., 23.5., and 29.5. at 8.30–11.45.
Learning outcomes: The aim of this course is to engage in intellectual dialogue, to develop a personal point of view on some of the central economic and political questions we face today, and to allow ourselves to think creatively, freely, and out of the box. After completing this course, students will have read important texts on new perspectives in economics and politics, they will have trained their ability to distill an own point of view from the writings of leading scientists, they will train their writing and discussion skills, and they will train to creatively apply what they have read in writing about the future of economics and politics in our society.
Lecture | |||||||
Introduction to the Course | 04.03.24 – 04.03.24 | Monday | 13:45 – 15:15 | L9, 1–2, Room 409 | |||
Lecture | 11.04.24 – 11.04.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 25.04.24 – 25.04.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 02.05.24 – 02.05.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 08.05.24 – 08.05.24 | Wednesday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 16.05.24 – 16.05.24 | Thursday | 08:30 – 11:45 | B6, 23–25, Room A301 | |||
Lecture | 23.05.24 – 23.05.24 | Thursday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||
Lecture | 29.05.24 – 29.05.24 | Wednesday | 08:30 – 11:45 | L9, 1–2, Room 409 | |||