GDAtools (version 1.6)

condesc: Measures the association between a continuous variable and some continuous and/or categorical variables

Description

Measures the association between a continuous variable and some continuous and/or categorical variables

Usage

condesc(y,x,min.cor=NULL)

Arguments

y

the continuous variable to describe

x

a data frame with continuous and/or categorical variables

min.cor

for the relationship between y and a categorical variable, only associations higher or equal to min.cor will be displayed. If NULL (default), they are all displayed.

Value

A list of the following items :

variables

associations between y and the variables in x, computed with BivariateAssoc function from package moreparty

categories

a data frame with categorical variables from x and associations measured by correlation coefficients

References

Rakotomalala R., 'Comprendre la taille d'effet (effect size)', [http://eric.univ-lyon2.fr/~ricco/cours/slides/effect_size.pdf]

See Also

condes, catdesc, assoc.yx, darma

Examples

# NOT RUN {
data(Taste)
getindexcat(Taste[,1:5])
mca <- speMCA(Taste[,1:5],excl=c(3,6,9,12,15))
condesc(mca$ind$coord[,1], Taste[,c('Gender','Age')])
# }