ltm (version 1.0-0)

rcor.test: Pairwise Associations between Items using a Correlation Coefficient

Description

Computes and tests the pairwise associations between items using a correlation coefficient

Usage

rcor.test(mat, p.adjust = FALSE, p.adjust.method = "holm", …)

Arguments

mat

a numeric matrix or a numeric data.frame containing the manifest variables as columns.

p.adjust

logical; if TRUE the \(p\)-values are adjusted for multiple comparisons.

p.adjust.method

the method argument of p.adjust().

…

extra arguments passed to cor() and cor.test().

Value

An object of class rcor.test with components,

cor.mat

the correlation matrix.

p.values

a three column numeric matrix containing the \(p\)-values for all the combinations of items.

The print method for class rcor.test returns a square matrix in which the upper diagonal part contains the estimates of the correlation coefficients, and the lower diagonal part contains the corresponding p-values.

Examples

# NOT RUN {
## pairwise associations for Environment data:
rcor.test(data.matrix(Environment), method = "kendall")

## pairwise associations for independent normal random variates:
mat <- matrix(rnorm(1000), 100, 10, dimnames = list(NULL, LETTERS[1:10]))
rcor.test(mat)
rcor.test(mat, method = "kendall")
rcor.test(mat, method = "spearman")

# }

Run the code above in your browser using DataCamp Workspace