Data is the first step in process of any statistical analysis. Since MDS has a bit different terms associated with data concepts and it can be confusing, I try to discuss the data used for MDS with terms that are more understandable or relevant to the common research setting.


Distance measures Measurement conditionality Number of ways Number of mode 


  1. Borg, I., & Groenen, P. J. F. (2005). Modern multidimensional scaling: Theory and applications (2nd ed.). New York, NY: Springer.zbMATHGoogle Scholar
  2. Coombs, C. H. (1964). A theory of data. New York, NY: Wiley.Google Scholar
  3. Coxon, A. P. M., Brier, A. P., & Hawkins, P. K. (2005). The New MDSX program series, version 5. Edinburgh/London: New MDSX Project.Google Scholar
  4. Davison, M. L. (1983). Multidimensional scaling. New York: Wiley.zbMATHGoogle Scholar
  5. MacKay, D. B., & Zinnes, J. (2014). PROSCAL professional: A program for probabilistic scaling:
  6. SAS Institute Inc. (2008). SAS/STAT® 9.2 User’s Guide. Cary, NC: SAS Institute Inc.Google Scholar
  7. Young, F. W. (1987). Multidimensional scaling: History, theory, and applications. In R. M. Hamer (Ed.), Multidimensional scaling: History, theory, and applications. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar

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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Cody S. Ding
    • 1
    • 2
  1. 1.Department of Education Science and Professional ProgramUniversity of Missouri-St. LouisSt. LouisUSA
  2. 2.Center for NeurodynamicsUniversity of Missouri-St. LouisSt. LouisUSA

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