Description Usage Arguments Details Value Author(s) References See Also Examples

Computes automatically P-values, Vtests, residuals, r-square for
each category of a given qualitative variable (e.g. the *panelist* variable);

Computes he agreement between each panelist and the panel results;

Gives the panel results (optional).

1 2 3 | ```
paneliperf(donnee, formul, formul.j = "~Product", col.j, firstvar,
lastvar = ncol(donnee), synthesis = FALSE, random = TRUE,
graph = FALSE)
``` |

`donnee` |
a data frame made up of at least two qualitative variables
( |

`formul` |
the aov model used for the panel |

`formul.j` |
the aov model used for each panelist (no |

`col.j` |
the position of the |

`firstvar` |
the position of the first endogenous variable |

`lastvar` |
the position of the last endogenous variable (by default the last column of |

`synthesis` |
boolean, the possibility to have the anova results for the panel model |

`random` |
boolean, the status of the Panelist variable in the anova model for the panel |

`graph` |
boolean, draws the PCA and MFA graphs |

The `formul`

parameter must be filled in by an analysis of variance model and must
begin with the categorical variable of interest (e.g. the product effect)
followed by the different other factors of interest (and their combinations).
E.g.:`formul = "~Product+Session"`

.

A list containing the following components:

`prob.ind` |
a matrix which rows are the panelist, which columns are the endogenous variables (in most cases the sensory descriptors) and which entries are the P-values associated to the AOV model |

`vtest.ind` |
a matrix which rows are the panelist, which columns are the endogenous variables (in most cases the sensory descriptors) and which entries are the Vtests associated to the AOV model |

`res.ind` |
a matrix which rows are the panelist, which columns are the endogenous variables (in most cases the sensory descriptors) and which entries are the residuals associated to the AOV model |

`r2.ind` |
a matrix which rows are the panelist, which columns are the endogenous variables (in most cases the sensory descriptors) and which entries are the R-square associated to the AOV model |

`signif.ind` |
a vector with the number of significant descriptors per panelist |

`agree.ind` |
a matrix with as many rows as there are panelists and as many columns as there are descriptors and the entries of this matrix are the correlation coefficients between the product coefficients for the panel and for the panelists |

`complete` |
a matrix with the v-test corresponding to the p.value (see |

`p.value` |
a matrix of dimension ( |

`variability` |
a matrix of dimension ( |

`res` |
a vector of dimension |

`r2` |
a vector of dimension |

The usual graphs when MFA is performed on the data.frame
resulting from vtest.ind and agree.ind.

The PCA graphs for the complete output.

F Husson, S Le

P. Lea, T. Naes, M. Rodbotten. *Analysis of variance for sensory data*.
H. Sahai, M. I. Ageel. *The analysis of variance*.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ```
## Not run:
data(chocolates)
res<-paneliperf(sensochoc, formul = "~Product+Panelist+Session+
Product:Panelist+Product:Session+Panelist:Session",
formul.j = "~Product", col.j = 1, firstvar = 5, synthesis = TRUE)
resprob<-magicsort(res$prob.ind, method = "median")
coltable(resprob, level.lower = 0.05, level.upper = 1,
main.title = "P-value of the F-test (by panelist)")
hist(resprob,main="Histogram of the P-values",xlab="P-values")
resr2<-magicsort(res$r2.ind, method = "median", ascending = FALSE)
coltable(resr2, level.lower = 0.00, level.upper = 0.85,
main.title = "Adjusted R-square (by panelist)")
resagree<-magicsort(res$agree, sort.mat = res$r2.ind, method = "median")
coltable(resagree, level.lower = 0.00, level.upper = 0.85,
main.title = "Agreement between panelists")
hist(resagree,main="Histogram of the agreement between panelist and panel",
xlab="Correlation coefficient between the product effect for
panelist and panel")
coltable(magicsort(res$p.value, sort.mat = res$p.value[,1], bycol = FALSE,
method = "median"),
main.title = "Panel performance (sorted by product P-value)")
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.