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

Computes automatically P-values associated with the F-test as well as the residual term for a given analysis of variance model.

1 2 |

`donnee` |
a data frame |

`formul` |
the model that is to be tested |

`subset` |
cf. function |

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

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

`random` |
boolean, effect should be possible as fixed or random (default as random) |

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:

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

`variability` |
a matrix of dimension ( |

`res` |
a vector of dimension |

`r2` |
a vector of dimension |

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 | ```
data(chocolates)
res=panelperf(sensochoc, firstvar = 5, formul = "~Product+Panelist+
Session+Product:Panelist+Session:Product+Panelist:Session")
## Sort results by product p.values.
coltable(magicsort(res$p.value, sort.mat = res$p.value[,1], bycol = FALSE,
method = "median"), main.title = "Panel performance (sorted by product P-value)")
``` |

```
Loading required package: FactoMineR
```

SensoMineR documentation built on Dec. 13, 2017, 9:04 a.m.

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