Organised by | The University of Manchester |
Presenter | Wendy Olsen (Professor of Socio-Economics) |
Date | 01/10/2018 |
Venue | University of Manchester |
Map | View in Google Maps (M13 9PL) |
Contact | CMI Short Courses [email protected] 0161 2751980 |
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. |
Level | Intermediate (some prior knowledge) |
Cost | £195 (£140 for those from educational, government and charitable institutions) |
Website and registration | |
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) |