A Factorial Approach for Sorting Task data (FAST)

By M. Cadoret, Sébastien Lê, Jérôme Pagès. 2009

97 citations recorded by the source corpus.

Subfields: Food Science, Nutrition and Dietetics, Sensory Systems

View Paper: https://www.semanticscholar.org/paper/fe7cd95f589b28e7d9922484f9e4f6a0063a163f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Food Science

1. Lynne J. Williams
2. Dominique Valentin
3. Paula Varela
4. G. Ares
5. Hervé Abdi
6. S. Jaeger
7. A. Giménez
8. Betina Piqueras-Fiszman

In Nutrition and Dietetics

1. Paula Varela
2. G. Ares
3. Dominique Valentin
4. Hervé Abdi
5. Lynne J. Williams

In Sensory Systems

1. Paula Varela
2. Hervé Abdi
3. Dominique Valentin
4. Lynne J. Williams
5. G. Ares

Citations in the corpus

• Sensory profiling, the blurred line between sensory and consumer science. A review of novel methods for product characterization (2012, methodology): “Cadoret et al. (2009) proposed the application of FAST for analyzing sorting data.”
• Invited review Quick and dirty but still pretty good: a review of new descriptive methods in food science (2012, unknown): “, 2007 ) , MCA ( Takane , 1982 ; Cadoret et al .”
• Multiple factor analysis: principal component analysis for multitable and multiblock data sets (2013, methodology): “The analysis of data sets with such a nested structure can be performed with the recently developed HMFA (see Refs 121,122, Ref 2 for a dual version, and Refs 26,29,30,54 for applications), that can be seen as an integration of MFA with the analysis of variance tradition.”