From MCA results, plots contributions to the axes.

```
barplot_contrib(resmca, dim = 1, which = "var",
sort = FALSE, col = "tomato4", repel = FALSE)
```

## Arguments

- resmca
object of class `MCA`

, `speMCA`

, `csMCA`

, `PCA`

or `CA`

- dim
the dimension to use. Default is 1.

- which
If `resmca`

is of class `MCA`

, `speMCA`

, `csMCA`

or `PCA`

, should be `"var"`

to plot contributions of variables or `"ind"`

to plot contributions of individuals. If `resmca`

is of class `CA`

, should be `"row"`

to plot contributions of rows or `"col"`

to plot contributions of columns. Default is `"var"`

.

- sort
logical. If `TRUE`

, bars are sorted by decreasing VIPs. Default is `FALSE`

.

- col
color of the bars

- repel
logical. If `TRUE`

, the names of the variables are repelled with `geom_text_repel`

. Default is `FALSE`

## Details

The contributions are multiplied by the sign of the coordinates, so that the plot shows on which side of the axis they contribute, which makes the interpretation easier.

## References

Le Roux B. and Rouanet H., *Multiple Correspondence Analysis*, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., *Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis*, Kluwer Academic Publishers, Dordrecht (June 2004).

## Examples

```
# specific MCA on the Music example data set
data(Music)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA")
mca <- speMCA(Music[,1:5], excl = junk)
# contributions of categories
barplot_contrib(mca)
```