assoc.twocat.by {descriptio}

Groupwise cross-tabulation and measures of association between two categorical variables

Description

Cross-tabulation and measures of association between two categorical variables, for each category of a group variable

Usage

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

Arguments

x

factor : the first categorical variable

y

factor : the second categorical variable

by

factor : the group variable

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 (asympt, default) or via Monte Carlo resampling (approx).

Value

A list of items, one for each category of the group variable. Each item is 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.twocat, assoc.catcont, assoc.twocont, assoc.yx, condesc, catdesc, darma

Examples

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