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.

multivariate, models, distribution, htest
corrcheck(marginal, support = list(), Spearman = FALSE)
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 of marginal will contain $k_i-1$ probabilities (the $k_i$-th is obviously 1 and shall not be included).
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 $1,2,...,k_i$
TRUE if we consider Spearman's correlation, FALSE (default) if we consider Pearson's correlation

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

  • corrcheck
# 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
Documentation reproduced from package GenOrd, version 1.4.0, License: GPL

Community examples

Looks like there are no examples yet.