Academic Writing

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Dirk Siepmann (University of Osnabrück)

Date: Thursday, 02/10/14 from 09.30-18.00 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The academic writing seminar comprises four modules:

  1. Word combining
  2. Sentence combining
  3. Academic style
  4. Academic correspondence

You have to register for the 8th International Research Workshop to participate in this course.

Network Analysis

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Dr. Per Kropp (Institute for Employment Research/IAB)

Date: Thursday, 02/10/14 from 09.30-18.00 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:

This course will familiarize students with basic concepts in social network analysis and its application. The focus will be on social networks as structure.. We will use the software package Pajek (the book edition: http://vlado.fmf.uni-lj.si/pub/networks/book/esna2.htm) to analyse centrality and prestige in networks, subgroup, and roles and positions.

Recommended literature and pre-readings:

  • De Nooy, W., A. Mrvar, et al. (2011). Exploratory Social Network Analysis with Pajek, Cambridge University Press.
  • Freeman, L. (2011): The Development of Social Network Analysis—with an Emphasis on Recent Events.  In J. Scott and P. J. Carrington (eds.) The SAGE Handbook of Social Network Analysis.London: SAGE Publications.

You have to register for the 8th International Research Workshop to participate in this course.

Introduction to MaxQDA

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Heiko Grunenberg (Leuphana University Lueneburg)

Date: Thursday, 02/10/14 from 09.30-18.00 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

MAXqda is a software to analyze textual data in a qualitative (but also quantitative) way. The course provides a basic introduction into the logic of the program and its broad possibilities. The goal is to enable you to use this tool accordingly to your own method of analysis. For this reason, everybody can practice our working-steps at an own Computer. We will start at the very beginning and learn about the basic features of the program such as preparation and import of texts, basic analysis strategies and creation of codes, memos and variables. After this, we will focus on analysis strategies, simple and complex text retrievals and strategies of mixed-method-designs.

Recommended literature and pre-readings:

Kuckartz., Udo (2014): Qualitative Text Analysis. Methods, Practice, Computer Assistance. London & Thousand Oaks: Sage Publications.

Lewins, Ann/Silver, Christina (2007): Using Software in Qualitative Research: A Step-By-Step Guide. SAGE: London.

You have to register for the 8th International Research Workshop to participate in this course.

Case Study Research

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Dr. Kamil Marcinkiewicz (University of Hamburg)

Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 14.30-18.00 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

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

Recommended literature and pre-readings:

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

You have to register for the 8th International Research Workshop to participate in this course.

Structural Equation Modelling with R

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Dr. Holger Steinmetz (University of Paderborn)

Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 09.00-12.30 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:

Structural equation models (SEMs) have become a powerful tool in the behavioral sciences to test hypotheses about relationships between variables and implications of causal structures. This workshop offers an introduction to the background, principles, opportunities, and limitations of SEMs. These issues are illustrated using the lavaan package (latent variable analysis) that is run within the free software platform R. Lavaan has recently become a serious competitor to commercial software packages and is delivers almost everything a user needs to perform SEM. Participation to the course requires some basic knowledge of regression analysis, variances, covariances of variables, and inferential statistics. Knowledge of R is not necessary.

Course topics cover:

  • A short treatment of causality (the counter factual approach) and introduction to causal models and their illustration with path diagrams / causal graphs.
  • The principle behind estimating parameters and basis for evaluation the adequacy of the model (e.g., chi-square test) including Wright’s path tracing rules and Pearls d-separation.
  • Treatment and modeling of latent variables and the connection to theoretical constructs.
  • Explanation of the lavaan syntax and exercises (modeling own data / models of the participants is appreciated).
  • Reasons for misfitting models, evaluation, diagnostics, and re-specification.
  • The problem of endogeneity and the valuable role of instrumental variables in SEMs.

Required packages to be installed:

  • psych
  • car
  • Hmisc
  • MASS
  • QuantPsyc
  • Boot
  • Mnormt
  • Pbivnorm
  • quadprog
  • simsem
  • lavaan

You have to register for the 8th International Research Workshop to participate in this course.

Qualitative Comparative Analysis (QCA) and Fuzzy Sets

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Jonas Buche, (Goethe-University Frankfurt)

Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 14.30-18.00 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

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

The course starts off from an introduction into the basics of QCA (sets, set memberships, set operations). Through the notion of necessary and sufficient conditions and of truth tables, the single elements are built into the Truth Table Algorithm. However, this algorithm is not free of problems. Therefore, some pitfalls and strategies how to overcome them are presented.

  1. The course is both conceptually and technically oriented. No prior knowledge is required.
  2. We will use the software fsQCA2.5 which can be downloaded at www.fsqca.com. Please note that the software does not operate on Apple Products!

Recommended literature and pre-readings:

  • Schneider, Carsten Q. and Claudius Wagemann (2012), Set-Theoretic Methods for the Social Sciences. Cambridge: Cambridge University Press.
  • Ragin, Charles C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. Chicago: University of Chicago Press.
  • Freitag, Markus, and Raphaela Schlicht. 2009. “Educational Federalism in Germany: Foundations of Social Inequality in Education.” Governance 22 (1): 47-72.
  • Emmenegger, Patrick. 2011. “Job Security Regulations in Western Democracies: A Fuzzy Set Analysis.” European Journal of Political Research 50 (3): 336-64.

You have to register for the 8th International Research Workshop to participate in this course.

Questionnaire Design

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Dr. Timo Lenzner (Gesis – Leibniz Institute for the Social Sciences)

Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 14.30-18.00 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The objective of this course is to give participants a thorough grounding in the psychological processes involved in answering survey questions and to introduce them to principles that can be applied to write effective survey questions. It covers the general principles of questionnaire design, question wording and construction of answer formats, special issues faced in writing factual, attitudinal and sensitive questions, and an introduction to various methods of questionnaire pretesting. Sessions combine lectures with practical exercises and discussion.

Please note that the course does not cover the psychometric principles of item or scale development. The course does not require any previous knowledge.

Recommended literature and pre-readings:

  • Krosnick, J. A. & Presser, S. (2010). Question and Questionnaire Design. In P. V. Marsden & J. D. Wright (Eds.), Handbook of Survey Research (2nd ed.) (pp. 263-313). Bingley: Emerald Group Publishing Limited.
  • Fowler, Floyd J., Jr. and Carol Cosenza (2008). “Writing effective survey questions”, in: De Leeuw, Edith D., Joop J. Hox and Don A. Dillman (eds.), The international handbook of survey methodology, Mahwah, NJ: Lawrence Erlbaum, pp. 136-160. (http://joophox.net/papers/SurveyHandbookCRC.pdf)
  • Schaeffer, Nora Cate and Stanley Presser. 2003. “The Science of Asking Questions.” Annual Review of Sociology, 29: 65-88.

You have to register for the 8th International Research Workshop to participate in this course.

Spatial and Panel Econometrics

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Assoc. Prof. Dr. Nisar Ahmad, Assoc. Prof. Time Friedel Mietze & Prof. Dr. Torben Dall Schmidt (University of Southern Denmark/Department of Border Region Studies)

Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 14.30-18.00 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

NB: Please bring your laptop computers with STATA installed on it.

The course is basically divided into two parts: Part 1) Analyzing panel data. Part 2) Spatial Data Analysis

Part 1): Structure of the Panel Data: This part of the course is an introduction to the panel data analysis and it provides some insights into why we use panel data. What kinds of models are available for panel data and how do we estimate such models. It also covers some extensions to the basic panel data models and finally there will be a session where you will learn how to estimate panel data using STATA.

Part 2): Spatial Data Analysis: In research fields such as regional science, quantitative sociology and business analysis as well as real estate, labor and health economics (to name just a few), researchers are increasingly aware of the fact that “space matters”. Thus, the goal of this workshop module is to equip participants with the basic knowledge about methods and tools currently available in “spatial statistics” and “spatial econometrics”. Besides presenting the general logic and theoretical foundations of these modeling approaches for variables with an explicit geographical context, a strong focus lies on illustrating the potential for applied work with these tools in the software package STATA. The module is structured as follows: After a brief introduction of the historical evolution of spatial data analysis, different research settings in economics and related research fields are outlined, which may call for the explicit use of spatial estimation techniques, for instance, in order to identify the importance of space-time autocorrelations and neighboring effects (spatial spillovers). Following this introduction, the concept of the spatial weighting matrix is introduced and statistical approaches to measure and visualize the degree of spatial dependence for a variable under study are presented. Moving from univariate to multivariate modeling techniques, the course then derives estimation techniques used in the field of spatial econometrics and links this theoretical knowledge with hands-on applications for different spatial datasets. Finally, to serve as an outlook on future research possibilities, state-of-the-art concepts such as spatial panel data models and spatial limited dependent variable models will be presented. Datasets and STATA ado-files will be provided ahead of the course and should be installed on the participants’ computers.

You have to register for the 8th International Research Workshop to participate in this course.

Introduction to Data Sets

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer:

SOEP: PD Dr. Elke Holst (German Institute for Economic Research/DIW Berlin)
ALLBUS: Dipl.-Soz. Michael Blohm (GESIS Leibniz Institute for the Social Sciences)
IAB Data: Dipl.-Vw. Stefan Seth (Institute for Employment Research/IAB)

Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 09.00-12.30 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Monday, 29/09/14: Introduction to the SOEP

The Socio-Economic Panel Study (SOEP) is a longitudinal study of private households in Germany. The panel provides information on all household members and was started in 1984. In 2011, there were more than 12,300 households with more than 21,000 persons sampled. Some of the many topics include household composition, occupational biographies, employment, earnings, health, wellbeing, integration, values, lifestyles, and personality. The course gives an overview of the data structure and the research designs facilitated by longitudinal household studies that go beyond conventional surveys (household analysis, intergenerational analysis, life course research, etc.). The course provides an applied introduction into the data retrieval via SOEPinfo.

Required: statistical knowledge, basic Stata or SPSS skills.

Recommended literature and pre-readings:

Tuesday, 30/09/14: Introduction to the ALLBUS

ALLBUS (Allgemeine Bevölkerungsumfrage der Sozialwissenschaften – German General Social Survey (GGSS)) is one of the foremost survey programs in Germany. It has been institutionalized as a part of GESIS – Leibniz Institute for the Social Sciences. The prototype for similar national data generation programs is the American General Social Survey (GSS).

Since 1980, ALLBUS/GGSS has provided a series of representative cross-sectional samples drawn from the adult population in Germany. These biennial surveys include partly replicative and partly innovative question modules and added value data for analyses of social structure, attitudes, values, and behavior in Germany. Moreover, users may find various possibilities for international comparisons. Currently, 19 ALLBUS/GGSS surveys (1980-2012) with a total of 57,723 respondents are available. A large part of the documentation has been translated into English.

In its first part the course gives an overview of the project as such. Basic sampling procedures, various question modules, and recent activities of the ALLBUS Research Data Center will be presented. The second part consists of hands-on exercises of chosen data. The analyses will be done primarily using Stata. Participants should have fundamental knowledge in data handling, in statistical data analysis and in using programs like Stata/SPSS via syntax. In addition, a report on the experience in ALLBUS/GGSS with Survey Nonresponse will be given.

Recommended literature and pre-readings:

  • Alba, Richard, Peter Schmidt and Martina Wasmer (eds.) 2003: Germans or Foreigners? Attitudes Towards Ethnic Minorities in Post-Reunification Germany, New York und Houndmills: Palgrave Macmillan.
  • Blohm, Michael, Franziska Lerch, Ute Hoffstätter, Katharina Schmidt and Daniel Nowack 2013: ALLBUS-Bibliographie (27. Fassung), GESIS – Technical Reports 2013|06.
  • Davis, James Allen, Peter Ph. Mohler and Tom W. Smith 1994: Nationwide General Social Surveys, in: Borg, Ingwer and Peter Ph. Mohler (eds.), Trends and Perspectives in Empirical Social Research, Berlin and New York: Walter de Gruyter: 17-25.
  • Smith, Tom W., Jibum Kim, Achim Koch and Alison Park 2005: Social-Science Research and the General Social Surveys, in: ZUMA-Nachrichten 56: 68-77.
  • Terwey, Michael 2000: ALLBUS: A German General Social Survey, in: Schmollers Jahrbuch 120: 151-158.
  • Terwey, Michael and Horst Baumann 2013: Variable Report German General Social Survey. ALLBUS / GGSS Cumulation 1980 – 2010, ZA-Study-No 4576, Cologne: GESIS, GESIS – Variable Reports No. 2013|2.

Wednesday, 01/10/14: Introduction to IAB Data

The Institute for Employment Research in Nuremberg has available a wealth of micro data on the German labor market and offers access to it in its Research Data Center (FDZ). The course’s goal is to arouse the participants’ interest in FDZ data and to guide their first steps into analyzing them. The focus will be on two large administrative data sets, namely the Sample of Integrated Employment Biographies (SIAB) and the Establishment History Panel (BHP). In hands-on sessions we will explore, cleanse and prepare the data, calculate durations, and implement simple imputation procedures. The course will also cover in some detail the IAB Establishment Panel, the FDZ’s most important survey data set, and the Linked Employer-Employee Dataset of the IAB (LIAB); other FDZ data will also be presented, but rather cursorily.

FDZ website
Overview of FDZ data

Basic to medium Stata skills required for the tutorial.

You have to register for the 8th International Research Workshop to participate in this course.

Expert Interviews

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Betina Hollstein (University of Hamburg)

Date: Monday, 29/09/14 – Wednesday, 01/10/14 from 09.00-12.30 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Expert interviews are often used in empirical social research. Sometimes they are part of the preparatory stage of a study. Sometimes expert interviews are the main data source. The course will focus on theory and practice of expert interviews, i.e. methodological foundations and practical considerations when conducting expert interviews.

The course starts out with a brief overview on the specific characteristics of qualitative data and methods. We will discuss problems and challenges associated with qualitative interviewing and different ways to deal with these challenges. We will address different types of expert interviews (guided interviews, narrative interview), by highlighting the strengths and weaknesses of each approach and discussing the crucial steps when preparing and conducting expert interviews. Finally, we will discuss how to get access to the field, ways of data management and different strategies for data analysis.

Required basic knowledge: Basic knowledge and skills in social research methods and methodology (Bachelor degree in a Social Science discipline).

You have to register for the 8th International Research Workshop to participate in this course.