Modelling changes over time in a multivariate paired comparison: An application to window display design. (February 2022)

• Record Type: Journal Article
• Authors: Grand, Alexandra; Dittrich, Regina
• Other Names: Francis Brian guest-editor.; Hinde John guest-editor.
• Is Part Of: Statistical modelling. Volume 22:Number 1/2(2022)
• Page Start: 95
• Page End: 106
• Publication Date: 2022-02
• Subjects: aesthetic judgements -- Judging change -- PC over time -- multivariate PC model of changes (MPCC); Linear models (Statistics) -- Periodicals; Mathematical models -- Periodicals; Modèles linéaires (Statistique) -- Périodiques; Modèles mathématiques -- Périodiques; Modèle statistique; Modèle linéaire; Modélisation statistique; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 519.5011
• DOI: 10.1177/1471082X21995675
• Languages: English
• ISSNs: 1471-082X

Abstract

This article proposes an alternative method of making comparative judgements in multivariate paired comparisons (PCs) where judgements about change are made directly by comparing an object at two time points for each of a series of attributes. The application deals with the design of shop window displays where products should be arranged by teams of vocational students according to aesthetic principles (attributes). The photos of the students' window displays at time 1 (before feedback) and at time 2 (after feedback) were compared by judging each attribute as to whether it was fulfilled better at time 1 or at time 2. An advantage of this PC approach over an alternative of a scoring system is the possibility to assess even subtle changes of various aspects of attractiveness, which cannot easily be measured using a score. To analyse these data, we used earlier work which developed both a multivariate PC pattern model for multi-attribute data and a PC model over time and defined a multivariate PC model of changes (MPCC). The model can be fitted as a non-standard Poisson log-linear model and provides estimates of change for the three attributes for time 2 and we were able to check for possible interaction effects between these attributes.