homog.test | R Documentation |

From MCA results, computes a homogeneity test for a categorical supplementary variable, i.e. characterizes the homogeneity of several subclouds.

homog.test(resmca, var, dim=c(1,2))

`resmca` |
object of class |

`var` |
the categorical supplementary variable. It does not need to have been used at the MCA step. |

`dim` |
the axes which are described. Default is c(1,2) |

Returns a list of lists, one for each selected dimension in the MCA. Each list has 2 elements :

`test.stat` |
The square matrix of test statistics |

`p.values` |
The square matrix of p.values |

Nicolas Robette

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).

`speMCA`

, `csMCA`

, `stMCA`

, `multiMCA`

, `textvarsup`

## Performs a specific MCA on 'Music' example data set ## ignoring every 'NA' (i.e. 'not available') categories, ## and then computes a homogeneity test for age supplementary variable. data(Music) getindexcat(Music) mca <- speMCA(Music[,1:5],excl=c(3,6,9,12,15)) homog.test(mca,Music$Age)

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