panelperf {SensoMineR}

Panel's performance according to its capabilities to dicriminate between products

Description

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

Usage

panelperf(donnee, formul, subset = NULL, firstvar, 
    lastvar = ncol(donnee), random = TRUE)

Arguments

donnee

a data frame

formul

the model that is to be tested

subset

cf. function lm in the stats package

firstvar

the position of the first endogenous variable

lastvar

the position of the last endogenous variable (by default the last column of donnee

random

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

Details

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".

Value

A list containing the following components:

p.value

a matrix of dimension (k,m) of P-values associated with the F-test for the k descriptors and the m factors and their combinations considered in the analysis of variance model of interest

variability

a matrix of dimension (k,m) where the entries correspond to the percentages of variability due to the effects introduced in the analysis of variance model of interest

res

a vector of dimension k of residual terms for the analysis of variance model of interest

r2

a vector of dimension k of r-squared for the analysis of variance model of interest

Author(s)

F Husson, S Le

References

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

See Also

paneliperf, aov

Examples

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)")