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Free-choice Profiling
Free-choice profiling is a method for determining the quality of a thing by having a large number of subjects experience (view, taste, read, etc.) it and then allowing them to describe the thing in their own words, as opposed to posing them a set of "yes-no-maybe" questions. All of the descriptions are then analyzed to determine a " consensus configuration" of qualities, usually through Generalized Procrustes analysis Generalized Procrustes analysis (GPA) is a method of statistical analysis that can be used to compare the shapes of objects, or the results of surveys, interviews, or panels. It was developed for analysing the results of free-choice profiling, a ... (GPA) or Multiple factor analysis (MFA). Free-choice profiling first emerged in 1984 but the original published model has been modified by researchers into variations that are more applicable to their particular use. For example, a technique employed by Jean Marc Sieffermann combined it with flash profiling, specificall ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generalized Procrustes Analysis
Generalized Procrustes analysis (GPA) is a method of statistical analysis that can be used to compare the shapes of objects, or the results of surveys, interviews, or panels. It was developed for analysing the results of free-choice profiling, a survey technique which allows respondents (such as sensory panelists) to describe a range of products in their own words or language. GPA is one way to make sense of free-choice profiling data; other ways can be multiple factor analysis (MFA), or the STATIS method. The method was first published by J. C. Gower in 1975. Generalized Procrustes analysis estimates the scaling factor applied to respondent scale usage, generating a weighting factor that is used to compensate for individual scale usage differences. Unlike measures such as a principal component analysis, GPA uses individual level data and a measure of variance is utilized in the analysis. The Procrustes distance provides a metric to minimize in order to superimpose a pair of s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multiple Factor Analysis
Multiple factor analysis (MFA) is a Factorial experiment, factorial method devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative and / or qualitative) structured in groups. It is a Multivariate statistics, multivariate method from the field of Ordination (statistics), ordination used to simplify Dimensionality reduction, multidimensional data structures. MFA treats all involved tables in the same way (symmetrical analysis). It may be seen as an extension of: * Principal component analysis (PCA) when variables are quantitative, * Multiple correspondence analysis (MCA) when variables are qualitative, * Factor analysis of mixed data (FAMD) when the active variables belong to the two types. Introductory example Why introduce several active groups of variables in the same factorial analysis? '' data'' Consider the case of quantitative variables, that is to say, within the framework of the PCA. An example of data from ecologic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
