, Volume 46, Issue 1, pp 9–28 | Cite as

Multidimensional successive categories scaling: A maximum likelihood method

  • Yoshio Takane


A single-step maximum likelihood estimation procedure is developed for multidimensional scaling of dissimilarity data measured on rating scales. The procedure can fit the euclidian distance model to the data under various assumptions about category widths and under two distributional assumptions. The scoring algorithm for parameter estimation has been developed and implemented in the form of a computer program. Practical uses of the method are demonstrated with an emphasis on various advantages of the method as a statistical procedure.

Key words

similarity ratings maximum likelihood multidimensional scaling (MDS) method of successive categories 


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Reference notes

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Copyright information

© The Psychometric Society 1981

Authors and Affiliations

  • Yoshio Takane
    • 1
  1. 1.Department of PsychologyMcGill UniversityMontrealCanada

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