SensoMineR (version 1.0)

fast: Factorial Approach for Sorting Task data

Description

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 to for the consumer j, or, in the case of "qualified" categorization, to the sequence of words associted to the group of which the product belongs to (i) for the consumer j.

Usage

fast(don,alpha=0.05,mot_min=2,graph=TRUE,ncp=5,B=200)

Arguments

don

a data frame with n rows (products) and p columns (assesor : categorical variables)

alpha

the confidence level of the ellipses

mot_min

minimum sample size for the word selection in textual analysis

graph

boolean, if TRUE a graph is displayed

ncp

number of dimensions kept in the results (by default 5)

B

the number of simulations (corresponding to the number of virtual panels) used to compute the ellipses

Value

• A list containing the following elements:
• eig
  a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance
• var
  a list of matrices containing all the results for the categories (coordinates, square cosine, contributions, v.test)
• ind
  a list of matrices containing all the results for the products (coordinates, square cosine, contributions)
• group
  a list of matrices containing all the results for consumers (coordinates, square cosine, contributions)
• cooccur
  the reordered co-occurrence matrix among products
• reord
  the reordered matrix products*consumers
• cramer
  the Cramer's V matrix between all the consumers
• call
  a list with some statistics

References

Cadoret, M., L^e, S., Pag`es, J. (2008) A novel Factorial Approach for analysing Sorting Task data. 9th Sensometrics meeting. St Catharines, Canada

Examples

data(perfume)
## Example of fast results
res.fast<-fast(perfume)