Flags pairs of items that behave redundantly in a network: their correlations
with all other items are mostly statistically indistinguishable (a small
proportion of significantly different correlations) and the two items are
themselves strongly correlated. Ported from networktools::goldbricker.
Usage
redundancy(
data,
p = 0.05,
threshold = 0.25,
cor_min = 0.5,
cor_method = c("auto", "pearson", "spearman", "kendall")
)Arguments
- data
A numeric data frame or matrix (rows = observations).
- p
Significance level for each pairwise correlation-difference test. Default 0.05.
- threshold
Maximum proportion of significantly different correlations for a pair to be flagged redundant. Default 0.25.
- cor_min
Minimum correlation between the two items themselves. Default 0.5.
- cor_method
Correlation type:
"auto"(default,cor_auto()- polychoric/polyserial as appropriate, matching goldbricker),"pearson","spearman", or"kendall".
Value
A tidy data.frame (class psychnet_redundancy), one row per flagged
pair (sorted most-redundant first), with columns item1, item2,
proportion (share of significantly different correlations) and
correlation. Zero rows when nothing is flagged. The full proportion matrix
is in attr(x, "proportion_matrix").