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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


  • Christine Daley



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

Suggested Citation

  • Hung-Wen Yeh & Byron Gajewski & David Perdue & Angel Cully & Lance Cully & K. Greiner & Won Choi & Christine Daley, 2014. "Sorting it out: pile sorting as a mixed methodology for exploring barriers to cancer screening," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2569-2587, September.
  • Handle: RePEc:spr:qualqt:v:48:y:2014:i:5:p:2569-2587
    DOI: 10.1007/s11135-013-9908-3

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    References listed on IDEAS

    1. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.
    2. J. Gower, 1975. "Generalized procrustes analysis," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 33-51, March.
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