This course is an introduction to Qualitative Comparative Analysis (QCA). QCA is a method for the comparative study of cases and is used to analyse qualitative social data systematically. The analysis compares cases by assigning set memberships across a set of attributes.
QCA is particularly good at understanding multiple causation because it is focused on causal recipes (combination of causes) rather than individual variables. This helps with understanding (different) causal pathways in policy evaluation settings.
The course will look at the theoretical and practical aspects of QCA, working through a detailed example using the fsQCA software package to understand crisp and fuzzy set QCA.
By the end of this session, participants will:
- Understand why and where QCA is a useful method
- Be able to prepare data for use in a QCA
- Have basic understanding of the fsQCA software for application for QCA
Corinna is a Reader in Computational Modelling at Glasgow University (MRC/CSO Social & Public Health Sciences Unit). Corinna is particularly interested in methodological and epistemological aspects of novel methods, in particular computational methods such as agent-based modelling and social simulation, and has published on aspects of ontology, explanatory power and context validity in modelling. As a computational modeller she has developed models of dynamic social networks of juvenile delinquency, neighbourhood effects of extortion racketeering and collective reasoning in social dilemma situations. She is particularly interested in complexity sensitive social science methods, comprising computational, case based and participatory methods. As a co-investigator in the Centre for Evaluation of Complexity Across the Nexus (CECAN) she is involved with developing these methods in a policy relevant way. She is currently working on how to combine methods through novel research designs.
£220 for Non-Members of UK Evaluation Society, £180 for Members, £140 for Student Members
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