Test association between correlation sturucture and variable

Score impact of each sample on correlation sturucture and then peform test of association with variable using Kruskal-Wallis test

Usage

delaneau.test(Y, variable, method = c("pearson", "kendall", "spearman"))

Arguments

Y

data matrix with samples on rows and variables on columns

variable

variable with number of entries must equal nrow(Y). Can be discrete or continuous.

method

specify which correlation method: "pearson", "kendall" or "spearman"

Value

list of p-value, estimate and method used

Details

The statistical test used depends on the variable specified. if variable is factor with multiple levels, use Kruskal-Wallis test if variable is factor with 2 levels, use Wilcoxon test if variable is continuous, use Wilcoxon test

See also

delaneau.score sle.test

Examples

# load iris data
data(iris)

# variable is factor with multiple levels
# use kruskal.test
delaneau.test( iris[,1:4], iris[,5] )
#> $p.value
#> [1] 5.648845e-05
#> 
#> $estimate
#> Kruskal-Wallis chi-squared 
#>                   19.56295 
#> 
#> $method
#> [1] "kruskal.test"
#> 

# variable is factor with 2 levels
# use wilcox.test
delaneau.test( iris[1:100,1:4], iris[1:100,5] )
#> $p.value
#> [1] 0.2510425
#> 
#> $estimate
#> [1] -0.0005950244
#> 
#> $method
#> [1] "wilcox.test"
#> 

# variable is continuous
# use cor.test with spearman
delaneau.test( iris[,1:4], iris[,1] )
#> $p.value
#> [1] 0.0504917
#> 
#> $estimate
#>        rho 
#> -0.1599965 
#> 
#> $method
#> [1] "cor.test"
#>