9th International Research Workshop “Methods for PhD” near Flensburg, September 27 – October 2, 2015

Empirical research is seeking through methodological processes to discover, hopefully, nontrivial facts and insights. Beside choosing a topic and grounding an idea in theory, empirical research consists of gathering and analysing data as well as presenting results in scientific contexts.

Our workshop tackles these steps of your research project:

  • Gathering data via (un)structured interviews or surveys and
  • using the computer for qualitative and quantitative data analysis.

The regular workshop fee is 439 Euro. It covers the participation in three courses, meals and accommodation. The workshop fee is 279 Euro without accommodation (only meals are included).

It is possible to get a certificate on 5 credit points (according to the European Credit Transfer System).

The following courses will be offered:

Parallel courses offered Monday and Tuesday morning (September 28/29):

  • Data Analysis with R
  • Data Analysis with Stata
  • Grounded Theory
  • Qualitative Interviews
  • Introduction to the SOEP and Applied Survival Analysis

Parallel courses offered Tuesday afternoon and Wednesday (September 29/30):

  • Analysing Panel and Spatial Data
  • Analysis of Qualitative Data and Exploratory Statistics
  • Questionnaire Design
  • Case Study Research
  • Structural Equation Modelling (SEM) with R

Parallel courses at the SDU (October 1):

  • Qualitative Comparative Analysis (QCA)
  • Academic Writing
  • Computable General Equilibrium (CGE) Modelling and Its Applications to Policy Impact Analysis
  • Measuring Preferences using Conjoint Analytic Methods
  • Introduction to Network Analysis

PLEASE note that the number of participants is limited to about 20 persons per course!

For further information, especially lecturers, program, organizers and registration visit our website.

For any questions don’t hesitate to contact the workshop committee.

The International Research Workshop is organised by

  • Prof. Dr. Wenzel Matiaske, Faculty of Economics and Social Sciences, Helmut-Schmidt-University/University of Federal Armed Forces and Research Professor at the German Institute for Economic Research (DIW Berlin)
  • Asst. Prof. Dr. Simon Fietze, Department of Border Region Studies, University of Southern Denmark, Campus Sønderborg
  • Dr. Heiko Stüber, Institute for Employment Research (IAB), The Research Institute of the Federal Employment Agency in Nuremberg

The workshop is supported by

  • Europa-Universität Flensburg
  • University of Hamburg, Faculty of Economics and Social Sciences
  • University of Hamburg, School of Business
  • Leuphana University Lüneburg, Faculty of Economics
  • Werkstatt für Personal- und Organisationsforschung e.V.
  • German Socio-Economic Panel Study (SOEP) at the DIW Berlin

Analysis of Qualitative Data and Exploratory Statistics

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Günter L. Huber & Dr. Leo Gürtler

Date: Tuesday, 29/09/15 (14:30 – 18:00) – Wednesday, 30/09/15 (09:00 – 18:00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The workshop starts with an overview on principal approaches to the analysis of qualitative data and demonstrates the implementation in the software package AQUAD Seven. Applying various sets of empiricaal data retrieval strategies, table analyses, code linkages and QCA are demonstrated. Selected techniques of exploratory data analysis in R show the advantages (and limits) of combining qualitative and quantitative methods. The participants are strongly invited to bring their own empirical data for further analyses.

You have to register for the 9th International Research Workshop to participate in this course.

Questionnaire Design

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tanja Kunz & Anke Metzler (Darmstadt University of Technology)

Date: Tuesday, 29/09/15 (14:30 – 18:00) – Wednesday, 30/09/15 (09:00 – 18:00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The course aims to provide an overview of the theoretical basics and empirical evidence related to questionnaire design. The cognitive process of survey responding, challenges of designing effective survey questions including aspects of proper question wording and optimal response formats, as well as pretest techniques for evaluating survey questions will be discussed. Special focus is on attitudinal and behavioral questions.

The course combines lectures with practical exercises. At the end of the course, participants will have comprehensive knowledge of the various aspects involved in designing and evaluating questionnaires.

Previous knowledge: Basic knowledge in quantitative social research methods

Recommended literature and pre-readings:

  • Dillman, D. A., Smith, J. D., & Christian, L. M. (2014). Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method. Hoboken, NJ: Wiley.
  • Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The Psychology of Survey Response. Cambridge University Press.

You have to register for the 9th International Research Workshop to participate in this course.

Academic Writing

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

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

Date: Thursday, 01/10/15 (09:30 – 18:00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Writing an academic text can be a daunting and complex task requiring knowledge of a range of accepted writing conventions as well as the ability to construct sentences that are idiomatically and grammatically correct. This course aims to highlight a range of important components in the writing process through analysis and practice using authentic academic texts. Topics covered include: academic style (formality, impersonal and objective language, passive voice, caution, nominalisation); structure at sentence, paragraph and document level; reporting verbs and their forms; coherence and cohesion.

Requirement of students: Please supply at least one week before the workshop begins an abstract or proposal for your research project, or a similar extract of academic text that you have written.

You have to register for the 9th International Research Workshop to participate in this course.

Case Study Research

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Kamil Marcinkiewicz (University of Hamburg)

Date: Tuesday, 29/09/15 (14:30 – 18:00) – Wednesday, 30/09/15 (09:00 – 18:00)

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 9th International Research Workshop to participate in this course.

Data Analysis with Stata

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tobias Gramlich (GESIS – Leibniz Institute of Social Sciences)

Date: Monday, 28/09/15 (09:00 – 18:00) – Tuesday, 29/09/15 (09:00 – 12:00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

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

For Beginners with no or very little Stata knowledge!

Course topics cover:

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

You have to register for the 9th International Research Workshop to participate in this course.

Qualitative Comparative Analysis (QCA)

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Jonas Buche, (Goethe-University Frankfurt)

Date: Thursday, 01/10/15 (09:30 – 18:00)

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 9th International Research Workshop to participate in this course.

Structural Equation Modeling (SEM) with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Holger Steinmetz (University of Paderborn)

Date: Tuesday, 29/09/15 (14:30 – 18:00) – Wednesday, 30/09/15 (09:00 – 18:00)

Max. number of participants: 25

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

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

Prerequisites for attending:

  • Basic knowledge of statistics (variance, co-variance) and regression analysis.

You have to register for the 9th International Research Workshop to participate in this course.

Data Analysis with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Michael Großbach (Hanover University of Music, Drama and Media)

Date: Monday, 28/09/15 (09:00 – 18:00) – Tuesday, 29/09/15 (09:00  – 12:00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Data analysis is one of the key skills for quantitative researchers. But data analysis is more than just your Stats 101 course in grad school. And it’s not only more I argue, it’s different. Data are not normal, there are outliers and missing values. Data often do not comply with our hypotheses. And yet we can learn from data, given the appropriate tools.

This course introduces the interactive and programmable statistical and graphics software environment R (http://www.r-project.org/), and the Integrated Development Environment RStudio (http://www.rstudio.com/) that provide a polished interface to R. The main topics will be reading data into R, exploratory data analysis – i.e. graphically scrutinising data -, data munging and, finally statistical analysis. Participants will build an ever-expanding knowledge of R as we go along.

Intermittently, participants will be given (anonymous) tests to allow for an evaluation of and give them feedback on their learning progress.

Prerequisites for attending:

  • A basic understanding of descriptive and (classic) inferential statistics would definitely be helpful
  • A laptop equipped with a wireless adaptor and a recent web browser

You have to register for the 9th International Research Workshop to participate in this course.

Measuring Preferences using Conjoint Analytic Methods and Advanced Compositional Approaches

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Assoc. Prof. Martin Meissner (University of Southern Denmark/Department of Environmental and Business Economics)

Date: Thursday, 01/10/15 (09:30 – 18:00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The participants of this course develop a sound understanding of the benefits of using conjoint analytic preferences measurement approaches and alternative advanced compositional approaches. Participants gain practical experience of using conjoint-analytic methods, and developed a better understanding of the value of measuring preferences.

The course starts with introducing the basic concepts behind the measurement of stated preferences, specifically focusing on conjoint analysis. The most often used approaches, i.e. traditional conjoint analysis, adaptive conjoint analysis and choice-based conjoint analysis are introduced. We deliberate on advantages and disadvantages of the approaches and also discuss advanced compositional approaches, like pairwise-comparison based preference measurement and the adaptive self-explicated approach. During the workshop we will further talk about all the important stages of designing a preference measurement study. We pay special attention to the types of research questions that conjoint analysis can answer. We also discuss the most important questions you should answer before setting up your preference measurement/conjoint study: What is the optimal choice of attributes and attribute level? What is a good experimental design? How should I design my survey design and present potential choice scenarios? How do I analyze the results?

Participants will have the opportunity to use Sawtooth Software on their own laptops and build their own conjoint analysis survey during the course. Based on this experience, participants will be able to improve the planning of their own future experiments.

Recommended literature and pre-readings:

  • Bradlow, Eric T. (2005), “Current Issues and a ‘Wish List’ for Conjoint Analysis,” Applied Stochastic Models in Business and Industry, 21 (4-5), 319-323.
  • Hauser, John R. and Vithala Rao (2003), “Conjoint Analysis, Related Modeling, and Applications,” in Advances in Marketing Research: Progress and Prospects, in Marketing Research and Modeling: Progress and Prospects, Wind, Jerry and Paul Green (eds.), New York: Springer, 141-168.

You have to register for the 9th International Research Workshop to participate in this course.