Fuzzy Set and QCA Analysis

Date:

02/02/2017

Organised by:

University of Manchester

Presenter:

Wendy Olsen

Level:

Intermediate (some prior knowledge)

Contact:

Michelle Kelly
cmist-courses@manchester.ac.uk
0161 275 4579

Map:

View in Google Maps  (M13 9PL)

Venue:

The University of Manchester
Humanities Bridgeford Street Building

Description:

Outline

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.

This one-day training course will attract those doing case-study research, those using the comparative research approaches, and those who want to extend their skills in QCA and fuzzy analysis from beginner to intermediate levels. It will suit qualitative researchers with no prior experience, as well as quantitative and mixed-methods researchers; all are welcome.  

Cost:

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

Website and registration:

Region:

North West

Keywords:

Qualitative Data Handling and Data Analysis, Qca , qualitative-comparative-analysis , fuzzy set analysis c , causal interpretation , dataset , fuzzify , calibrate , consistency

Related publications and presentations:

Qualitative Data Handling and Data Analysis

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