The analysis of dependence for three ways contingency tables with ordinal variables: A case study of patient satisfaction data

Biagio Simonetti, Eric Beh () and Luigi D'Ambra

Journal of Applied Statistics, 2010, vol. 37, issue 1, 91-103

Abstract: For many questionnaires and surveys in the marketing, business, and health disciplines, items often involve ordinal scales (such as the Likert scale and rating scale) that are associated in sometimes complex ways. Techniques such as classical correspondence analysis provide a simple graphical means of describing the nature of the association. However, the procedure does not allow the researcher to specify how one item may be associated with another, nor does the analysis allow for the ordinal structure of the scales to be reflected. This article presents a graphical approach that can help the researcher to study in depth the complex association of the items and reflect the structure of the items. We will demonstrate the applicability of this approach using data collected from a study that involves identifying major factors that influence the level of patient satisfaction in a Neapolitan hospital.

Keywords: correspondence analysis; orthogonal polynomials; patient satisfaction evaluation (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1080/02664760802653552

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