Recovery of subsampled dimensions and configurations derived from napping data by MFA and MDS

Napping is a multivariate sensory method in which participants physically place stimuli on a large sheet of paper and orient them so that the distance between pairs represents a measure of dissimilarity. The two-dimensional nature of the task may be a limitation to the ability of this and similar methodologies to recover information about complex stimuli. In the first investigation, eight simulated three-dimensional stimuli were created with two different levels for each attribute. Simulated napping experiments had groups of participants attend to two of the dimensions with different probabilities. Multiple factor analysis (an analytical multivariate statistical procedure that can be thought of as a principle components analysis on the individuals) and MDS-INDSCAL (a variation on multidimensional scaling that finds a common configuration through reducing a stress measure associated with lack of fit) recovered full dimensionality from these data, although MFA had trouble when attention was the most unbalanced. In the second experiment, a human napping experiment was designed using custom three-dimensional stimuli: shapes with two levels each of size, color, and shape attributes. This experiment confirmed the results of Experiment 1, as both MDS-INDSCAL and MFA analyses again recovered the full dimensionality of the stimuli.

[1]  Jérôme Pagès,et al.  ANÁLISIS FACTORIAL MÚLTIPLE: PRINCIPALES CARACTERÍSTICAS Y SU APLICACIÓN A DATOS SENSORIALES , 2004 .

[2]  H. Lawless Exploration of fragrance categories and ambiguous odors using multidimensional scaling and cluster analysis , 1989 .

[3]  Pauline Faye,et al.  Perceptive free sorting and verbalization tasks with naive subjects: an alternative to descriptive mappings , 2004 .

[4]  Dominique Valentin,et al.  Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications , 2007 .

[5]  P. Robert,et al.  A Unifying Tool for Linear Multivariate Statistical Methods: The RV‐Coefficient , 1976 .

[6]  Jérôme Pagès,et al.  Collection and analysis of perceived product inter-distances using multiple factor analysis: Application to the study of 10 white wines from the Loire Valley , 2005 .

[7]  J. Chang,et al.  Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition , 1970 .

[8]  Harry T. Lawless,et al.  Perceptual mapping of citrus juices using projective mapping and profiling data from culinary professionals and consumers , 2008 .

[9]  D. Ennis Confusable and discriminable stimuli: Comment on Nosofsky (1986) and Shepard (1986). , 1988 .

[10]  Sébastien Lê,et al.  A Factorial Approach for Sorting Task data (FAST) , 2009 .

[11]  R. Shepard Attention and the metric structure of the stimulus space. , 1964 .

[12]  R. Nosofsky Attention, similarity, and the identification-categorization relationship. , 1986, Journal of experimental psychology. General.

[13]  Moonja P. Kim,et al.  The Method of Sorting as a Data-Gathering Procedure in Multivariate Research. , 1975, Multivariate behavioral research.

[14]  Einar Risvik,et al.  Evaluation of sensory profiling and projective mapping data , 1997 .

[15]  Harry T. Lawless,et al.  Perceptual mapping of apples and cheeses using projective mapping and sorting. , 2010 .

[16]  Harry T. Lawless,et al.  Sensory Evaluation of Food: Principles and Practices , 1998 .

[17]  J. Tukey,et al.  Multiple-Factor Analysis , 1947 .

[18]  F. J. Pérez Elortondo,et al.  Projective mapping in sensory analysis of ewes milk cheeses: A study on consumers and trained panel performance , 2004 .

[19]  Garmt Dijksterhuis Multivariate data analysis in sensory and consumer science , 1997 .

[20]  Lawrence E. Jones,et al.  The effects of random error and subsampling of dimensions on recovery of configurations by non-metric multidimensional scaling , 1974 .

[21]  Einar Risvik,et al.  Projective mapping: A tool for sensory analysis and consumer research , 1994 .

[22]  Harry T. Lawless,et al.  Sensory Evaluation of Food , 1999 .

[23]  Harry T. Lawless,et al.  UNDERSTANDING MOUTHFEEL ATTRIBUTES: A MULTIDIMENSIONAL SCALING APPROACH , 1993 .

[24]  John W. Hall,et al.  Comparison of projective mapping and sorting data collection and multivariate methodologies for identification of similarity-of-use of snack bars , 1998 .

[25]  Forrest W. Young,et al.  Introduction to Multidimensional Scaling: Theory, Methods, and Applications , 1981 .

[26]  R. Shepard Discrimination and generalization in identification and classification: Comment on Nosofsky. , 1986 .