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A Novel Sequential Mixed-method Technique for Contrastive Analysis of Unscripted Qualitative Data

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  • Laura Y. Cabrera
  • Peter B. Reiner

Abstract

Between-subject design surveys are a powerful means of gauging public opinion, but critics rightly charge that closed-ended questions only provide slices of insight into issues that are considerably more complex. Qualitative research enables richer accounts but inevitably includes coder bias and subjective interpretations. To mitigate these issues, we have developed a sequential mixed-methods approach in which content analysis is quantitized and then compared in a contrastive fashion to provide data that capitalize upon the features of qualitative research while reducing the impact of coder bias in analysis of the data. This article describes the method and demonstrates the advantages of the technique by providing an example of insights into public attitudes that have not been revealed using other methods.

Suggested Citation

  • Laura Y. Cabrera & Peter B. Reiner, 2018. "A Novel Sequential Mixed-method Technique for Contrastive Analysis of Unscripted Qualitative Data," Sociological Methods & Research, , vol. 47(3), pages 532-548, August.
    • Handle: RePEc:sae:somere:v:47:y:2018:i:3:p:532-548
    DOI: 10.1177/0049124116661575
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    1. repec:cup:judgdm:v:8:y:2013:i:3:p:202-213 is not listed on IDEAS
    2. Anthony Onwuegbuzie, 2003. "Effect Sizes in Qualitative Research: A Prolegomenon," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(4), pages 393-409, November.
    3. Link, B.G. & Phelan, J.C. & Bresnahan, M. & Stueve, A. & Pescosolido, B.A., 1999. "Public conceptions of mental illness: Labels, causes, dangerousness, and social distance," American Journal of Public Health, American Public Health Association, vol. 89(9), pages 1328-1333.
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