Automatic correlation matrix (polychoric / polyserial / Pearson)

Detects ordinal variables (integer-valued with at most ordinal_max_levels levels) and returns the correlation matrix using a polychoric correlation for ordinal-ordinal pairs, a polyserial correlation for ordinal-continuous pairs, and Pearson otherwise, projected to the nearest positive-definite matrix. The base-R counterpart of qgraph::cor_auto(); this is the correlation bootnet/qgraph use by default for Likert data.

Usage

cor_auto(data, ordinal_max_levels = 7L, na_method = c("pairwise", "listwise"))

Arguments

data

Numeric data frame or matrix (rows = observations).

ordinal_max_levels

Maximum distinct values for a variable to count as ordinal. Default 7.

na_method

"pairwise" (default) or "listwise".

Value

A correlation matrix with the variable names as dimnames.

Examples

set.seed(1)
z <- matrix(stats::rnorm(300 * 4), 300, 4) %*% chol(0.5^abs(outer(1:4, 1:4, "-")))
x <- apply(z, 2, function(col) as.integer(cut(col, 5)))   # 5-level Likert
cor_auto(x)
#>            V1        V2        V3         V4
#> V1 1.00000000 0.4542199 0.2843910 0.09885485
#> V2 0.45421990 1.0000000 0.4944493 0.32126907
#> V3 0.28439095 0.4944493 1.0000000 0.50448731
#> V4 0.09885485 0.3212691 0.5044873 1.00000000