# multiMCA: Performs Multiple Factor Analysis In GDAtools: A Toolbox for Geometric Data Analysis and More

 multiMCA R Documentation

## Performs Multiple Factor Analysis

### Description

Performs Multiple Factor Analysis, drawing on the work of Escoffier and Pages (1994). It allows the use of MCA variants (e.g. specific MCA or class specific MCA) as inputs.

### Usage

`multiMCA(l_mca, ncp = 5, compute.rv = FALSE)`

### Arguments

 `l_mca` a list of objects of class `MCA`, `speMCA` or `csMCA` `ncp` number of dimensions kept in the results (default is 5) `compute.rv` whether RV coefficients should be computed or not (default is FALSE, which makes the function execute faster)

### Details

This function binds individual coordinates from every MCA in `l_mca` argument, weights them by the first eigenvalue, and the resulting data frame is used as input for Principal Component Analysis (PCA).

### Value

Returns an object of class `'multiMCA'`, i.e. a list:

 `eig` a list of numeric vector for eigenvalues, percentage of variance and cumulative percentage of variance `var` a list of matrices with results for input MCAs components (coordinates, correlation between variables and axes, square cosine, contributions) `ind` a list of matrices with results for individuals (coordinates, square cosine, contributions) `call` a list with informations about input data `VAR` a list of matrices with results for categories and variables in the input MCAs (coordinates, square cosine, test-values, variances) `my.mca` lists the content of the objects in `l_mca` argument `RV` a matrix of RV coefficients

Nicolas Robette

### References

Escofier, B. and Pages, J. (1994) "Multiple Factor Analysis (AFMULT package)". Computational Statistics and Data Analysis, 18, 121-140.

`plot.multiMCA`, `varsup`, `speMCA`, `csMCA`, `MFA`, `PCA`

### Examples

```## Performs a specific MCA on music variables of 'Taste' example data set,
## another one on movie variables of 'Taste' example data set,
## and then a Multiple Factor Analysis.
data(Taste)
getindexcat(Taste[,1:5])
mca1 <- speMCA(Taste[,1:5],excl=c(3,6,9,12,15))
getindexcat(Taste[,6:11])
mca2 <- speMCA(Taste[,6:11],excl=c(3,6,9,12,15,18))
mfa <- multiMCA(list(mca1,mca2))
plot.multiMCA(mfa)
```

GDAtools documentation built on March 18, 2022, 5:13 p.m.