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)