Category Archives: Quantitative Methods

Mixed Methods

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Udo Kelle & Dr. Elke Goltz (Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg)

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

Max. number of participants: 22

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The course will give an overview about current debates regarding the integration of qualitative and quantitative methods in social research and about the most important (agreed-upon and contested) issues in the field. We will discuss different forms of mixed methods, reasons for using such designs and criteria for the assessment of the quality of designs and findings from mixed methods studies. Since mixed methods designs are used to compensate for specific limitations of qualitative or quantitative (mono)methods special emphasis is laid on problems of qualitative and quantitative research –problems of operationalization and measurement, problems of statistical inference, of generalizability and sampling, of (causal) explanation, theory testing and theory generation, both in qualitative and quantitative research. We will demonstrate how such problems can be detected and dealt with in a mixed methods design. Finally, it will be shown how qualitative and quantitative findings from a mixed methods study can be meaningfully integrated and how convergent, contradictory and complementary findings can be dealt with.

Required basic knowledge: Basic knowledge and skills in social research methods and methodology (qualitative and quantitative) equivalent to the level of a Bachelor degree in a Social Science discipline

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.

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.

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.

Data Analysis with Stata

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Dipl.-Verw. Wiss. Tobias Gramlich (University of Duisburg-Essen)

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:

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 8th International Research Workshop to participate in this course.

Data Analysis with R

Institution: see Organisers & Acknowledgements

Programme of study: International Research Workshop

Lecturer: Dr. Marco Lehmann (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:

The course introduces the programming language R used for statistical analyses. The beginning of each lecture comes with a demonstration of programming and statistical functions that will be elaborated in the course of study. The students will then practice with many statistical examples. In addition to statistical functions the course will introduce the definition of R as a programming language and its syntax rules. Students will further learn to use R’s scripting capabilities. Successful participation requires basic knowledge in descriptive and inferential statistics. The students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed.

Recommended literature and pre-readings:

  • Wollschläger, Daniel (2012). Grundlagen der Datenauswertung mit R (2. Aufl.). Berlin: Springer.

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

Weiterbildung: How to Design a Mixed Methods Research with Validity

The workshop will take place from 9:00 a.m. till 1 p.m., on Wednesday, 19th of March 2014 in Aula at Helmut-Schmidt-University / University of the Federal Armed Forces of Germany (Hamburg)

The primary purpose of this workshop is to introduce workshop attendees to mixed methods research (MMR). An emphasis will be placed on high quality design and validity issues in mixed methods research.  A secondary purpose is to discuss with workshop attendees how mixed methods research can be used to address their research interests and research questions.

Dr. Burke Johnson will briefly cover the following topics, but he will emphasize research design and validity issues:

  • Introduction and definitions of MMR
  • Intellectual history of MMR
  • Philosophies and paradigms in MMR
  • Three major types of MMR: Quantitatively driven, qualitatively driven, and interactive MMR
  • Research questions
  • Major methods of data collection in empirical research
  • Major research methods in quantitative, qualitative, and mixed methods research
  • Sampling methods in MMR
  • Validity or legitimation design in MMR
  • How to determine the dimensions for designing an MMR research study
  • Data analysis in MMR
  • Report writing and publishing in MMR.

Please find further information on the course and application on this website.

Einführung in die Biografientypisierung mit der Sequenzmusteranalyse

Einführung in die Biografientypisierung mit der Sequenzmusteranalyse

Am 15. und 16.01.2014 findet an der Helmut-Schmidt-Universität Hamburg ein Seminar unter dem Titel “Einführung in die Biografientypisierung mit der Sequenzmusteranalyse” statt.

Die Sequenzmusteranalyse liefert einen empirischen Ansatz, der den Grad der Verschiedenheit von Lebensläufen ins Zentrum rückt. Im Mittelpunkt des Forschungsinteresses steht der Lebensweg. Die unterschiedlichen Lebenswege sollen als Ganzes analysiert und eventuelle Lebenswegmuster entwickelt werden.

Im Seminar werden die Sequenzmusteranalyse und die Clusteranalyse als Verfahren zur Typisierung behandelt. Für die Analyse kommen dabei die Programme R (freeware) und SPSS zum Einsatz.

Zeitplanung:
Mittwoch, 15. Januar 2014, 09:00 – 17.30 Uhr
Donnerstag, 16. Januar 2014, 09:00 – 12.30 Uhr

Eine Anmeldung ist bis zum 14. Januar möglich – die Zahl der Teilnehmenden ist auf 20 Personen begrenzt. Detaillierte Informationen zur Anmeldung erhalten Sie unter diesem Link.