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.
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 ki values, the i-th element of marginal will contain ki−1 probabilities (the ki-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,...,ki
Spearman: TRUE if we consider Spearman's correlation, FALSE (default) if we consider Pearson's correlation
Returns
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)
Author(s)
Alessandro Barbiero, Pier Alda Ferrari
See Also
contord, ordcont, ordsample
Examples
# four variablesk <-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 rhocorrcheck(marginal, Spearman=TRUE)# lower and upper bounds for Spearman's rho# change the supportssupport <- 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