assoc.catcont.by.RdMeasures the association between a categorical variable and a continuous variable, for each category of a group variable
assoc.catcont.by(x, y, by, weights = NULL,
na.rm.cat = FALSE, na.value.cat = "NAs", na.rm.cont = FALSE,
nperm = NULL, distrib = "asympt", digits = 3)factor : the categorical variable
numeric vector : the continuous variable
factor : the group variable
numeric vector of weights. If NULL (default), uniform weights (i.e. all equal to 1) are used.
logical, indicating whether NA values in the categorical variable (i.e. x) should be silently removed before the computation proceeds. If FALSE (default), an additional level is added to the categorical variable (see na.value.cat argument).
character. Name of the level for NA category. Default is "NAs". Only used if na.rm.cat = FALSE.
logical, indicating whether NA values in the continuous variable (i.e. y) should be silently removed before the computation proceeds. Default is FALSE.
numeric. Number of permutations for the permutation test of independence. If NULL (default), no permutation test is performed.
the null distribution of permutation test of independence can be approximated by its asymptotic distribution ("asympt", default) or via Monte Carlo resampling ("approx".
integer. The number of digits (default is 3).
A list of items, one for each category of the group variable. Each item is a list with the following elements :
summary statistics (mean, median, etc.) of the continuous variable for each level of the categorical variable
eta-squared between the two variables
p-value from a permutation (i.e. non-parametric) test of independence
point biserial correlation between the two variables, for each level of the categorical variable
permutation p-value of the correlation between the two variables, for each level of the categorical variable
test-values as proposed by Lebart et al (1984)
p-values corresponding to the test-values
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.
data(Movies)
with(Movies, assoc.catcont.by(Country, Budget, ArtHouse, nperm = 10))
#> $summary
#> $summary$No
#> mean sd min q1 median q3 max mad
#> Europe 41671103 45507234 1225500 11846500 21242000 53513500 163400000 13072000
#> France 10424753 15243974 48614 3765522 6786520 12123204 181621894 3881661
#> Other 40713833 36884079 6536000 10212500 24510000 65768500 103759000 17157000
#> USA 45751512 41015270 306375 17974000 32680000 61275000 245100000 16340000
#>
#> $summary$Yes
#> mean sd min q1 median q3 max mad
#> Europe 5672953 7578134 500.000 1225500 3300000 8170000 40850000 2575000
#> France 3482859 4691170 29500.000 931055 2090000 3999990 50052027 1425910
#> Other 6218257 13796434 40850.000 1260405 2532700 4493500 65360000 1429750
#> USA 18295864 16213239 0.817 6127500 11846500 30433250 57190000 10702700
#>
#>
#> $eta.squared
#> $eta.squared$No
#> [1] 0.208907
#>
#> $eta.squared$Yes
#> [1] 0.2438707
#>
#>
#> $permutation.pvalue
#> $permutation.pvalue$No
#> [1] 0
#>
#> $permutation.pvalue$Yes
#> [1] 0
#>
#>
#> $cor
#> $cor$No
#> Europe France Other USA
#> 0.083 -0.456 0.029 0.399
#>
#> $cor$Yes
#> Europe France Other USA
#> 0.023 -0.370 0.032 0.485
#>
#>
#> $cor.perm.pval
#> $cor.perm.pval$No
#> Europe France Other USA
#> 1.284732e-01 1.183400e-33 4.641500e-01 0.000000e+00
#>
#> $cor.perm.pval$Yes
#> Europe France Other USA
#> 2.312261e-01 1.041704e-16 4.135296e-01 9.026113e-14
#>
#>
#> $test.values
#> $test.values$No
#> Europe France Other USA
#> 1.8813621 -10.3287728 0.6506543 9.0330668
#>
#> $test.values$Yes
#> Europe France Other USA
#> 0.5127832 -8.1477652 0.6960400 10.6896674
#>
#>
#> $test.values.pval
#> $test.values.pval$No
#> Europe France Other USA
#> 0.05992267 0.00000000 0.51526969 0.00000000
#>
#> $test.values.pval$Yes
#> Europe France Other USA
#> 6.081030e-01 4.440892e-16 4.864038e-01 0.000000e+00
#>
#>