Statistical Methods and Applications

, Volume 16, Issue 2, pp 263–278

Two-step PLS regression for L-structured data: an application in the cosmetic industry

  • Vincenzo Esposito Vinzi
  • Christiane Guinot
  • Silvia Squillacciotti
Original Article

DOI: 10.1007/s10260-006-0028-2

Cite this article as:
Vinzi, V.E., Guinot, C. & Squillacciotti, S. Stat. Meth. & Appl. (2007) 16: 263. doi:10.1007/s10260-006-0028-2

Abstract

The present paper proposes a PLS-based methodology for the study of so called “L” data-structures, where external information on both the rows and the columns of a dependent variable matrix is available. L-structures are frequently encountered in consumer preference analysis. In this domain it may be desirable to study the influence of both product and consumer descriptors on consumer preferences. The proposed methodology has been applied on data from the cosmetic industry. The preference scores from 142 consumers on 9 products were explained with respect to the products’ physico-chemical and sensory descriptors, and the consumers’ socio-demographic and behavioural characteristics.

Keywords

Partial least squares (PLS) regressionPreference dataExternal informationL-structures

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Vincenzo Esposito Vinzi
    • 1
    • 2
  • Christiane Guinot
    • 4
  • Silvia Squillacciotti
    • 1
    • 3
    • 4
  1. 1.University of Naples “Federico II”NaplesItaly
  2. 2.ESSEC Business SchoolCergy-PontoiseFrance
  3. 3.EDF R&D – Département ICAMEClamartFrance
  4. 4.CE.R.I.E.S.Biometrics and Epidemiology UnitNeuilly-sur-SeineFrance