Nonlinear programming approach to optimal scaling of partially ordered categories
 Shizuhiko Nishisato,
 P. S. Arri
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A modified technique of separable programming was used to maximize the squared correlation ratio of weighted responses to partially ordered categories. The technique employs a polygonal approximation to each singlevariable function by choosing mesh points around the initial approximation supplied by Nishisato's method. The major characteristics of this approach are: (i) it does not require any grid refinement; (ii) the entire process of computation quickly converges to the acceptable level of accuracy, and (iii) the method employs specific sets of mesh points for specific variables, whereby it reduces the number of variables for the separable programming technique. Numerical examples were provided to illustrate the procedure.
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 Title
 Nonlinear programming approach to optimal scaling of partially ordered categories
 Journal

Psychometrika
Volume 40, Issue 4 , pp 525548
 Cover Date
 19751201
 DOI
 10.1007/BF02291554
 Print ISSN
 00333123
 Online ISSN
 18600980
 Publisher
 SpringerVerlag
 Additional Links
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 Authors

 Shizuhiko Nishisato ^{(1)}
 P. S. Arri
 Author Affiliations

 1. The Ontario Institute for Studies in Education, Canada