Modelling Trends in Ordered Correspondence Analysis Using Orthogonal Polynomials

Psychometrika. 2016 Jun;81(2):325-49. doi: 10.1007/s11336-015-9448-y. Epub 2015 Mar 20.

Abstract

The core of the paper consists of the treatment of two special decompositions for correspondence analysis of two-way ordered contingency tables: the bivariate moment decomposition and the hybrid decomposition, both using orthogonal polynomials rather than the commonly used singular vectors. To this end, we will detail and explain the basic characteristics of a particular set of orthogonal polynomials, called Emerson polynomials. It is shown that such polynomials, when used as bases for the row and/or column spaces, can enhance the interpretations via linear, quadratic and higher-order moments of the ordered categories. To aid such interpretations, we propose a new type of graphical display-the polynomial biplot.

Keywords: bivariate moment decomposition; generalized singular value decomposition; hybrid decomposition; polynomial biplots; symmetric and non-symmetric correspondence analysis.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Health Status
  • Humans
  • Middle Aged
  • Models, Statistical*
  • Psychometrics
  • Statistics as Topic*
  • Young Adult