Perform Factorial Approach for Sorting Task data (FAST) on a table where the rows (i) are products and the columns (j) are consumers. A cell (i,j) corresponds either to the number of the group to which the product i belongs for the consumer j, or, in the case of "qualified" categorization, to the sequence of words associted with the group to which the product i belongs for the consumer j.
fast(don,alpha=0.05,sep.words=" ",word.min=5,graph=TRUE,axes=c(1,2),
ncp=5,B=200,label.miss=NULL,ncp.boot=NULL)A list containing the following elements:
a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance
a list of matrices containing all the results for the categories (coordinates, square cosine, contributions, v.test)
a list of matrices containing all the results for the products (coordinates, square cosine, contributions)
a list of matrices containing all the results for consumers (coordinates, square cosine, contributions)
all the results of the MCA
the reordered co-occurrence matrix among products
the reordered matrix products*consumers
the Cramer's V matrix between all the consumers
the results of the textual analysis for the products
a list with some statistics
a data frame with n rows (products) and p columns (assesor : categorical variables)
the confidence level of the ellipses
the word separator character in the case of qualified categorization
minimum sample size for the word selection in textual analysis
boolean, if TRUE a graph is displayed
a length 2 vector specifying the components to plot
number of dimensions kept in the results (by default 5)
the number of simulations (corresponding to the number of virtual panels) used to compute the ellipses
label associated with missing groups in the case of incomplete data set
number of dimensions used for the Procrustean rotations to build confidence ellipses (by default NULL and the number of components is estimated)
Marine Cadoret, Sebastien Le sebastien.le@institut-agro.fr
Cadoret, M., Le, S., Pages, J. (2008) A novel Factorial Approach for analysing Sorting Task data. 9th Sensometrics meeting. St Catharines, Canada
Cadoret, M., Le, S., Pages, J. (2009) A Factorial Approach for Sorting Task data (FAST). Food Quality and Preference. 20. pp. 410-417
Cadoret, M., Le, S., Pages, J. (2009) Missing values in categorization. Applied Stochastic Models and Data Analysis (ASMDA). Vilnius, Lithuania
if (FALSE) {
data(perfume)
## Example of FAST results
res.fast<-fast(perfume,sep.words=";")
res.consensual<-ConsensualWords(res.fast)
}
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