assoc.twocat {descriptio} | R Documentation |

## Cross-tabulation and measures of association between two categorical variables

### Description

Cross-tabulation and measures of association between two categorical variables

### Usage

```
assoc.twocat(x, y, weights = NULL, na.rm = FALSE, na.value = "NA",
nperm = NULL, distrib = "asympt")
```

### Arguments

`x` |
the first categorical variable (must be a factor) |

`y` |
the second categorical variable (must be a factor) |

`weights` |
numeric vector of weights. If NULL (default), uniform weights (i.e. all equal to 1) are used. |

`na.rm` |
logical, indicating whether NA values should be silently removed before the computation proceeds. If FALSE (default), an additional level is added to the variables (see na.value argument). |

`na.value` |
character. Name of the level for NA category. Default is "NA". Only used if na.rm = FALSE. |

`nperm` |
numeric. Number of permutations for the permutation test of independence. If NULL (default), no permutation test is performed. |

`distrib` |
the null distribution of permutation test of independence can be approximated by its asymptotic distribution ( |

### Value

A list of lists with the following elements :

`tables`

list :

`freq` |
cross-tabulation frequencies |

`prop` |
percentages |

`rprop` |
row percentages |

`cprop` |
column percentages |

`expected` |
expected values |

`global`

list :

`chi.squared` |
chi-squared value |

`cramer.v` |
Cramer's V between the two variables |

`permutation.pvalue` |
p-value from a permutation (i.e. non-parametric) test of independence |

`global.pem` |
global PEM |

`GK.tau.xy` |
Goodman and Kruskal tau (forward association, i.e. x is the predictor and y is the response) |

`GK.tau.yx` |
Goodman and Kruskal tau (backward association, i.e. y is the predictor and x is the respons) |

`local`

list :

`std.residuals` |
the table of standardized (i.e.Pearson) residuals. |

`adj.residuals` |
the table of adjusted standardized residuals. |

`adj.res.pval` |
the table of p-values of adjusted standardized residuals. |

`odds.ratios` |
the table of odds ratios. |

`local.pem` |
the table of local PEM |

`phi` |
the table of the phi coefficients for each pair of levels |

`phi.perm.pval` |
the table of permutation p-values for each pair of levels |

`gather`

: a data frame gathering informations, with one row per cell of the cross-tabulation.

### Note

The adjusted standardized residuals are strictly equivalent to test-values for nominal variables as proposed by Lebart et al (1984).

### Author(s)

Nicolas Robette

### References

Agresti, A. (2007). *An Introduction to Categorical Data Analysis*, 2nd ed. New York: John Wiley & Sons.

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

Lebart L., Morineau A. and Warwick K., 1984, *Multivariate Descriptive Statistical Analysis*, John Wiley and sons, New-York.

### See Also

`assoc.catcont`

, `assoc.twocont`

, `assoc.yx`

, `condesc`

,
`catdesc`

, `darma`

### Examples

```
data(Movies)
assoc.twocat(Movies$Country, Movies$ArtHouse, nperm=100)
```

*descriptio*version 1.3 Index]