Classification trees for multivariate ordinal response: an application to Student Evaluation Teaching

Mariangela Sciandra (), Antonella Plaia () and Vincenza Capursi ()
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Mariangela Sciandra: University of Palermo
Antonella Plaia: University of Palermo
Vincenza Capursi: University of Palermo

Quality & Quantity: International Journal of Methodology, 2017, vol. 51, issue 2, No 11, 655 pages

Abstract: Abstract Data from multiple items on an ordinal scale are commonly collected when qualitative variables, such as feelings, attitudes and many other behavioral and health-related variables are observed. In this paper we introduce a method to derive a distance-based tree for multivariate ordinal response that allows, when subject-specific characteristics are available, to derive common profiles for respondents giving the same/similar multivariate ratings. Special attention will be paid to the performance comparison in terms of AUC, for three different distances used as splitting criteria. Simulated data an a dataset from a Student Evaluation of Teaching survey will be used as illustrative examples. The latter will be used to show the performance of the procedure in profiling students by identifying which features of their experience are most closely related to their expressed satisfaction.

Keywords: Decision tree; Ordinal response; Student Evaluation of Teaching; Distances (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11135-016-0430-2

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