Mason, W.J., Mirza, N. and Webb, C. (2018) Using the Framework Method to Analyze Mixed-Methods Case Studies. In: SAGE Research Methods Cases. Sage Publications ISBN 9781526438683
Abstract
This case study seeks to introduce readers to framework analysis as a means of organising and synthesising mixed methods data. By offering a practical description of framework analysis in action we hope to offer guidance on the application of the technique, alongside evidencing its utility for researchers managing large and unwieldly data sets. The research discussed in this article involved six mixed methods case studies of social work decision making. Case studies were located in England and Scotland and focused on the interplay between families’ socio-economic circumstances and social workers’ decisions to intervene where there were child protection concerns. These case studies were part of a broader four nations UK comparison of the relationship between area level deprivation and child welfare intervention rates (www.coventry.ac.uk/cwip). Framework analysis was adapted by the authors to manage the complex mixed methods data these case studies produced. Through a critical discussion of the strengths and weaknesses encountered using framework analysis, focusing on issues of coding transparency, team working, data integration, organisation and fragmentation, we elucidate the methodological benefits and drawbacks that researchers might bear in mind when considering the use of framework analysis in social research.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 SAGE Publications. |
Dates: |
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Institution: | The University of Sheffield |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Jan 2018 14:43 |
Last Modified: | 29 Jan 2018 14:43 |
Published Version: | https://doi.org/10.4135/9781526438683 |
Status: | Published |
Publisher: | Sage Publications |
Refereed: | Yes |
Identification Number: | 10.4135/9781526438683 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:126670 |