Correlation network

Marginal (zero-order) association network: the Pearson correlation matrix with the diagonal removed. Equivalent to bootnet's "cor" default.

Usage

cor_network(
  data = NULL,
  cor_matrix = NULL,
  n = NULL,
  cor_method = c("pearson", "spearman", "kendall", "auto"),
  threshold = 0,
  alpha = NULL,
  adjust = "none",
  na_method = c("pairwise", "listwise"),
  labels = NULL
)

Arguments

data

Numeric data frame or matrix (rows = observations). Optional if cor_matrix is supplied.

cor_matrix

Optional precomputed correlation matrix; if given, data is ignored and n is required when alpha is used.

n

Sample size (needed for significance testing when cor_matrix is supplied).

cor_method

Correlation method: "pearson" (default), "spearman", "kendall", or "auto" (polychoric/polyserial for ordinal items, the qgraph::cor_auto default; see cor_auto()).

threshold

Correlations with absolute value below this are set to zero. Default 0.

alpha

Significance level; if set, correlations not significant at alpha are zeroed. NULL (default) keeps every edge.

adjust

Multiple-comparison adjustment for the edge p-values (any stats::p.adjust method). Default "none".

na_method

Missing-data handling: "pairwise" (default) uses pairwise-complete correlations projected to the nearest positive-definite matrix; "listwise" drops rows with any NA. Identical when data is complete.

labels

Optional node labels.

Value

A psychnet object whose $weights is the thresholded correlation matrix, with $cor_matrix, $n_eff, $na_method (and $p_values when alpha is used).

Examples

x <- matrix(stats::rnorm(200 * 4), 200, 4)
cor_network(x)
#> <psychnet> cor network
#>   nodes: 4   edges: 6   (undirected)
cor_network(x, alpha = 0.05, adjust = "BH")
#> <psychnet> cor network
#>   nodes: 4   edges: 0   (undirected)