ekomex: Introduction to Qualitative Comparative Analysis (QCA)

Inhalt 

This five-day online course introduces Qualitative Comparative Analysis (QCA) as a set-theoretic technique for comparing intermediate to large numbers of cases that models causal complexity to analyze necessary or sufficient conditions for an outcome, covering its main assumptions, standard procedures, operations, and technical application.

What Is This Course About?
Qualitative Comparative Analysis (QCA) is a set-theoretic technique for comparing intermediate to large numbers of cases that models causal complexity to analyze necessary or sufficient conditions for an outcome. This five-day online course introduces QCA as an approach and a technique, its main assumptions, its standard procedures and operations, and the technical environment used for its application. Participants gain a thorough understanding of the formal logic of set-theoretic methods and QCA, including topics such as Boolean algebra, causal complexity, sets and their calibration, necessity, and sufficiency. The course discusses the logic and analysis of truth tables and the most important problems that emerge when this analytical tool is used for exploring social science data. Right from the beginning, participants are exposed to performing set-theoretic analyses with the relevant R software packages using data from published applications in the social sciences.

Timetable

  • Mornings: 90’ of prerecorded lectures, quizzes, and other learning materials for independent consumption
  • 11:30-12:30h:  Small group work (participants work on exercises assigned the previous day)
  • 14:00-15.00h: Office hours (participants can book individual slots via a sign-up sheet)
  • 15.30-17.00h: Live online session on zoom (Q&A on conceptual matters, Lab exercises in R)


Learning Goals
In this course you will

  • Gain a thorough understanding of the general analytic goals and motivations underlying the use of QCA.
  • Gain a thorough understanding of the formal logic underlying QCA, as well as of the notions of sets, causal complexity, necessity, and sufficiency.
  • Be able to perform the main analytic steps involved in doing a QCA (calibration, analysis of necessity, analysis of sufficiency) using the relevant R software packages and social science data.
  • Be able to identify potential pitfalls and problems that might emerge in applied QCA together with ways of avoiding them.
  • Be able to interpret and visualize QCA results.


Who are Your Instructors?
Ioana-Elena Oana is a Research Fellow at the European University Institute (EUI) focusing on comparative politics, political representation, political behavior, and public opinion formation. She is the main developer of the R package SetMethods for QCA and has extensive experience in teaching QCA using R at various international methods schools and universities (IQMR, ECPR, IPSA-Flacso, etc.). She has co-authered the book ‘Qualitative Comparative Analysis (QCA) using R: A Beginner’s Guide’ (Cambridge University Press, 2021, with Carsten Q. Schneider and Eva Thomann) and ‘A Robustness Test Protocol for Applied QCA: Theory and R Software Application’ (Sociological Methods & Research, 2021, with Carsten Q. Schneider).
Website: https://nenaoana.github.io
Twitter: @NenaOana

Carsten Q. Schneider is Professor of Political Science and Pro-Rector for External Relations at Central European University (CEU). He is author of three books on Qualitative Comparative Analysis (QCA) and a fourth one forthcoming with Cambridge University Press on set-theoretic multi-method research. Over the past two decades, Schneider has taught numerous methods courses in Europe, the US, and Latin America.
Website: https://people.ceu.edu/carsten-q_schneider
Twitter: @CarstenQSchneid

Bildungszeit 
Anforderungen des Bildungszeitgesetzes Baden-Württemberg sind erfüllt
Ihre Investition 
460 EUR / Early bird 390 EUR / Please note: you will gain access to our learning management system Moodle only after having paid your course fee
ECTS Credits 
4
Kontakt für Fragen 
Termin 
06.03.2023 (ganztägig)
07.03.2023 (ganztägig)
08.03.2023 (ganztägig)
09.03.2023 (ganztägig)
10.03.2023 (ganztägig)
Datum Details 
This intensive 1-week course over 5 days entails 4h of online teaching activities per day plus online office hour, including a mixture of asynchronous and synchronous elements and small-group work. Moreover, students should plan for sufficient time to do the assigned daily homework and read the assigned literature in advance.
Voraussetzungen 
Participation in the introduction course to R is recommended.