Fuzzy Set and QCA Analysis

Description:

Qualitative Comparative Analysis is a systematic method of studying data on multiple comparable cases from about N=8 through to large datasets of N=10,000 etc. The QCA methods firstly involve casing, i.e. delineating cases; secondly organising a systematic data matrix (we will show these in NVIVO and in Excel); thirdly examining sets of cases known as configurations; fourth interpreting these in terms of ‘necessary cause’ and ‘sufficient cause’ of each major outcome of interest.  We demonstrate the fsQCA software for QCA. A fuzzy set is a record of the membership score of a case in a characteristic or set.  A crisp set is a membership value of 0 (not in the set) or 1 (fully in the set), and thus is a simplified measure compared with a fuzzy set. Fuzzy sets or crisp sets, and combinations, can be used in QCA.  All the permutations of the causal factors, known as X variates, are considered one by one.  We test whether X is necessary, or sufficient, or both, for an outcome Y.  We then augment the standard measures of ‘consistency’.  We show that one can generate both within-group and sample-wide consistency levels for testing sufficient cause.

Cost:

£195 (£140 for those from educational, government and charitable institutions)

Website and registration:

https://www.cmist.manchester.ac.uk/study/short/list/

Region:

North West

Keywords:

Evaluation Research, Analysis of existing survey data, Qualitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, Mixed Methods Approaches (other), Qca , qualitative , comparative analysis , fuzzy set analysis , dataset , mixed-methods , multiple-methods , triangulation , evaluation methods

Related publications and presentations:

Evaluation Research
Analysis of existing survey data
Qualitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
Mixed Methods Approaches (other)

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