GenOrd (version 1.3.0)

corrcheck: Checking correlations for feasibility

Description

The function returns the lower and upper bounds of the correlation coefficients of each pair of ordinal/discrete variables given their marginal distributions, i.e., returns the range of feasible bivariate correlations.

Usage

corrcheck(marginal, support = list(), Spearman = FALSE)

Arguments

marginal

a list of $k$ elements, where $k$ is the number of variables. The $i$-th element of marginal is the vector of the cumulative probabilities defining the marginal distribution of the $i$-th component of the multivariate variable. If the $i$-t

support

a list of $k$ elements, where $k$ is the number of variables. The $i$-th element of support contains the ordered values of the support of the $i$-th variable. By default, the support of the $i$-th variable is $1,2,...,k_i$

Spearman

TRUE if we consider Spearman's correlation, FALSE (default) if we consider Pearson's correlation

Value

• The functions returns a list of two matrices: the former contains the lower bounds, the latter the upper bounds of the feasible pairwise correlations (on the extra-diagonal elements)

See Also

contord, ordcont, ordsample

Examples

# four variables
k <- 4
# with 2, 3, 4, and 5 categories (Likert scales, by default)
kj <- c(2,3,4,5)
# and these marginal distributions (set of cumulative probabilities)
marginal <- list(0.4, c(0.6,0.9), c(0.1,0.2,0.4), c(0.6,0.7,0.8,0.9))
corrcheck(marginal) # lower and upper bounds for Pearson's rho
corrcheck(marginal, Spearman=TRUE) # lower and upper bounds for Spearman's rho
# change the supports
support <- list(c(0,1), c(1,2,4), c(1,2,3,4), c(0,1,2,5,10))
corrcheck(marginal, support=support) # updated bounds