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Regular version of the site
Master 2019/2020

Comparative Research Designs and Methods

Type: Elective course (Comparative Social Research)
Area of studies: Sociology
Delivered by: School of Sociology
When: 2 year, 1 module
Mode of studies: distance learning
Instructors: Christian Fröhlich
Master’s programme: Comparative Soсial Research
Language: English
ECTS credits: 4
Contact hours: 2

Course Syllabus

Abstract

This course is part of the IPSAMOOC project, a joint venture Federica Weblearning - IPSA, the International Political Science Association. This course provides an introduction and overview of systematic comparative analysis in the social sciences, and shows you how to use this method for constructive explanation and theory building. A major portion of the course is devoted to new approaches and software that have been developed in recent years to handle highly complex cases. The course is a Massive Open Online Course delivered at Coursera platform ( online courses and take an oral examination at HSE for completing the course. The examination is taken after completion of the course during examination week. The full syllabus is published at the course websites. (https://www.edx.org/course/comparative-research-designs-and-methods-0). Basic quantitative or qualitative methodological training will be useful, but participants with little methodological training should find no major obstacles to following the course. Only for students of Comparative Social Research programme
Learning Objectives

Learning Objectives

  • An understanding of systematic comparative analysis and why it is more useful than other broad-based statistical methods
  • How to use systematic comparative analysis for constructive explanation and theory building
  • How to apply systematic comparative analysis to real-world politics
Expected Learning Outcomes

Expected Learning Outcomes

  • to get familiar with basic rules of five "canons" by John Stuart Mill
  • to be able tor fit of the data, being closer to the real values.
Course Contents

Course Contents

  • Week 1. Multidimensional substance matter and mills canon's
    History of comparative analysis.
  • Week 2. Further Advances, Comparative Research Designs
    Most similar and most different designs. Matching and Contrasting of Cases
  • Week 3. Introduction to Boolean Algebra, main steps of QCA
    QCA applications, troubleshooting, Multi-Value QCA (mv-QCA)
  • Week 4. Fuzzy set analyses, basic features
    Fuzzy set applications (fs/qca)
  • Week 5. Macro-quantitative (statistical) Methods
    Conclusions and Perspectives
Assessment Elements

Assessment Elements

  • Partially blocks (final) grade/grade calculation After attending the MOOC it is required to present the final results (certificate/another document).
  • non-blocking Oral exam
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    After attending the MOOC it is required to present the final results (certificate or another document - C). The document has to be submitted to the study office immediately after completion of the course. After successful completion of the course an examination is undertaken. Prerequisite for attending the examination is submission of the certificate to the study office. The examination grade (E) is the final grade for the course. Final control: oral group exam. The overall course grade (G) (10-point scale) is calculated as a sum of G = C*0.7+ E*0.3
Bibliography

Bibliography

Recommended Core Bibliography

  • Sykes, B., Verma, A., & Hancock, B. (2018). Aligning sampling and case selection in quantitative-qualitative research designs: Establishing generalizability limits in mixed-method studies. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edssch&AN=edssch.oai%3aescholarship.org%2fark%3a%2f13030%2fqt74j5p4dz
  • Thyer, B. A. (2012). Quasi-Experimental Research Designs. New York: Oxford University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=422245

Recommended Additional Bibliography

  • Fletcher, J. M., & Conley, D. (2013). The Challenge of Causal Inference in Gene–Environment Interaction Research: Leveraging Research Designs From the Social Sciences. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B8A5A729
  • Schenker, J. D., & Rumrill, J. . P. D. (2004). Causal-comparative research designs. Journal of Vocational Rehabilitation, 21(3), 117–121. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=16012317