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Use of multiple cluster analysis methods to explore the validity of a community outcomes concept map

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  • Orsi, Rebecca

Abstract

Concept mapping is now a commonly-used technique for articulating and evaluating programmatic outcomes. However, research regarding validity of knowledge and outcomes produced with concept mapping is sparse. The current study describes quantitative validity analyses using a concept mapping dataset. We sought to increase the validity of concept mapping evaluation results by running multiple cluster analysis methods and then using several metrics to choose from among solutions. We present four different clustering methods based on analyses using the R statistical software package: partitioning around medoids (PAM), fuzzy analysis (FANNY), agglomerative nesting (AGNES) and divisive analysis (DIANA). We then used the Dunn and Davies-Bouldin indices to assist in choosing a valid cluster solution for a concept mapping outcomes evaluation. We conclude that the validity of the outcomes map is high, based on the analyses described. Finally, we discuss areas for further concept mapping methods research.

Suggested Citation

  • Orsi, Rebecca, 2017. "Use of multiple cluster analysis methods to explore the validity of a community outcomes concept map," Evaluation and Program Planning, Elsevier, vol. 60(C), pages 277-283.
    • Handle: RePEc:eee:epplan:v:60:y:2017:i:c:p:277-283
    DOI: 10.1016/j.evalprogplan.2016.08.017
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    References listed on IDEAS

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    1. Rosas, Scott R. & Kane, Mary, 2012. "Quality and rigor of the concept mapping methodology: A pooled study analysis," Evaluation and Program Planning, Elsevier, vol. 35(2), pages 236-245.
    2. Dumont, Jeanne, 1989. "Validity of multidimensional scaling in the context of structured conceptualization," Evaluation and Program Planning, Elsevier, vol. 12(1), pages 81-86, January.
    3. Trochim, William M. K., 1989. "An introduction to concept mapping for planning and evaluation," Evaluation and Program Planning, Elsevier, vol. 12(1), pages 1-16, January.
    4. McLinden, Daniel, 2013. "Concept maps as network data: Analysis of a concept map using the methods of social network analysis," Evaluation and Program Planning, Elsevier, vol. 36(1), pages 40-48.
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    4. McLinden, Daniel, 2017. "And then the internet happened: Thoughts on the future of concept mapping," Evaluation and Program Planning, Elsevier, vol. 60(C), pages 293-300.

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