Estimation of interaction coefficients

Description

Computes automatically the interaction coefficients between two quantitative variables col.p and col.j for the following model: "~col.p+col.j+col.p:col.j".

Usage

1
interact(donnee, col.p, col.j, firstvar, lastvar = ncol(donnee))

Arguments

donnee

a data frame made up of at least two qualitative variables (product, panelist) and a set of quantitative variables (sensory descriptors)

col.p

the position of the product effect for instance

col.j

the position of the panelist effect for instance

firstvar

the position of the first endogenous variable

lastvar

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

Details

In most cases col.p represents the product effect, col.j represents the panelist effect, and the variables of interest are the sensory descriptors. The model considered is the following one: "~Product+Panelist+Product:Panelist".
Data must be complete (but not necessarily balanced).

Value

Returns an array of dimension (p,j,k), where p is the number of products, j the number of panelists and k the number of sensory descriptors. The entries of this array are the interaction coefficients between a panelist and a product for a given descriptor.
For each sensory descriptor, returns a graph where each (panelist,product) interaction coefficient is displayed, a graph where the contribution to the (panelist,product) interaction coefficient by product is displayed, a graph where the contribution to the (panelist,product) interaction coefficient by panelist is displayed.

Author(s)

Fran<e7>ois Husson

See Also

aov

Examples

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## Not run: 
data(chocolates)
resinteract=interact(sensochoc, col.p = 4, col.j = 1, firstvar = 5)

## End(Not run)

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