التفاصيل البيبلوغرافية
| العنوان: |
A cluster differences unfolding method for large datasets of preference ratings on an interval scale: Minimizing the mean squared centred residuals |
| المؤلفون: |
Macías, Rodrigo, Vera, J. Fernando, Heiser, Willem J. |
| المساهمون: |
Consejo Nacional de Ciencia y Tecnología, European Regional Development Fund |
| المصدر: |
British Journal of Mathematical and Statistical Psychology ; volume 77, issue 2, page 356-374 ; ISSN 0007-1102 2044-8317 |
| بيانات النشر: |
Wiley |
| سنة النشر: |
2024 |
| المجموعة: |
Wiley Online Library (Open Access Articles via Crossref) |
| الوصف: |
Clustering and spatial representation methods are often used in combination, to analyse preference ratings when a large number of individuals and/or object is involved. When analysed under an unfolding model, row‐conditional linear transformations are usually most appropriate when the goal is to determine clusters of individuals with similar preferences. However, a significant problem with transformations that include both slope and intercept is the occurrence of degenerate solutions. In this paper, we propose a least squares unfolding method that performs clustering of individuals while simultaneously estimating the location of cluster centres and object locations in low‐dimensional space. The method is based on minimising the mean squared centred residuals of the preference ratings with respect to the distances between cluster centres and object locations. At the same time, the distances are row‐conditionally transformed with optimally estimated slope parameters. It is computationally efficient for large datasets, and does not suffer from the appearance of degenerate solutions. The performance of the method is analysed in an extensive Monte Carlo experiment. It is illustrated for a real data set and the results are compared with those obtained using a two‐step clustering and unfolding procedure. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| DOI: |
10.1111/bmsp.12332 |
| الاتاحة: |
http://dx.doi.org/10.1111/bmsp.12332 |
| Rights: |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
| رقم الانضمام: |
edsbas.2F696B49 |
| قاعدة البيانات: |
BASE |