Sorting it out: pile sorting as a mixed methodology for exploring barriers to cancer screening

Hung-Wen Yeh (), Byron Gajewski (), David Perdue (), Angel Cully (), Lance Cully (), K. Greiner (), Won Choi () and Christine Daley ()

Quality & Quantity: International Journal of Methodology, 2014, vol. 48, issue 5, 2569-2587

Abstract: We discuss a mixed methodology for analyzing pile sorting data. We created a list of 14 barriers to colon cancer screening and recruited 18, 13, and 14 participants from three American Indian (AI) communities to perform pile sorting. Quantitative data were analyzed by cluster analysis and multidimensional scaling. Differences across sites were compared using permutation bootstrapping. Qualitative data collected during sorting were compiled by AI staff members who determined names for the clusters found in quantitative analysis. Results showed five clusters of barriers in each site although barriers in the clusters varied slightly across sites. Simulation demonstrated type I error rates around the nominal 0.05 level whereas power depended on the numbers of clusters, and between and within cluster variability. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Pile sorting; Multivariable; Cluster analysis; Multidimensional scaling; Permutation bootstrapping (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11135-013-9908-3

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