# 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 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.

### Usage

1 |

### Arguments

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

`alpha` |
the confidence level of the ellipses |

`sep.words` |
the word separator character in the case of qualified categorization |

`word.min` |
minimum sample size for the word selection in textual analysis |

`graph` |
boolean, if TRUE a graph is displayed |

`axes` |
a length 2 vector specifying the components to plot |

`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 |

`val` |
boolean, if TRUE elements of validity are calculating (it is time consuming) |

`B.val` |
the number of simulations used to obtain the elements of validity |

`label.miss` |
label associated with missing groups in the case of incomplete data set |

### 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) |

`acm` |
all the results of the MCA |

`cooccur` |
the reordered co-occurrence matrix among products |

`reord` |
the reordered matrix products*consumers |

`cramer` |
the Cramer's V matrix between all the consumers |

`textual` |
the results of the textual analysis for the products |

`validity` |
the elements of validity calculated for the first eigenvalue and the ellipses |

`call` |
a list with some statistics |

### Author(s)

Marine Cadoret, S\'ebastien L\^e sebastien.le@agrocampus-ouest.fr

### 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

Cadoret, M., L\^e, S., Pag\'es, J. (2009) *A Factorial Approach for Sorting Task data (FAST)*. Food Quality and Preference. 20. pp. 410-417

Cadoret, M., L\^e, S., Pag\'es, J. (2009) *Missing values in categorization*. Applied Stochastic Models and Data Analysis (ASMDA). Vilnius, Lithuania

### Examples

1 2 3 4 5 6 |