corrcheck
From GenOrd v1.4.0
by Alessandro Barbiero
Checking correlations for feasibility
The function returns the lower and upper bounds of the correlation coefficients of each pair of discrete variables given their marginal distributions, i.e., returns the range of feasible bivariate correlations.
 Keywords
 multivariate, models, distribution, htest
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 $i$th component can take $k_i$ values, the $i$th element ofmarginal
will contain $k_i1$ probabilities (the $k_i$th is obviously 1 and shall not be included).  support

a list of $k$ elements, where $k$ is the number of variables. The $i$th element of
support
is the vector containing 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 extradiagonal elements)
See Also
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
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