Permutation test for whether two groups' Gaussian graphical models differ,
on three invariants: global strength (M), maximum edge difference (S),
and per-edge differences (E). Networks are EBIC graphical lassos (clean-room
pure R). Equivalent in purpose to NetworkComparisonTest::NCT().
Usage
net_compare(
data1,
data2 = NULL,
iter = 1000L,
gamma = 0.5,
paired = FALSE,
abs = TRUE,
weighted = TRUE,
p_adjust = "none"
)Arguments
- data1, data2
Numeric data frames/matrices with the same columns.
- iter
Number of permutations. Default 1000.
- gamma
EBIC hyperparameter. Default 0.5.
- paired
Logical; within-row swapping for paired designs. Default FALSE.
- abs
Logical; compare absolute edge weights. Default TRUE.
- weighted
Logical; if FALSE, binarize networks first. Default TRUE.
- p_adjust
Multiple-comparison adjustment for per-edge p-values (any stats::p.adjust method). Default
"none".
Value
An object of class psychnet_nct with $nw1, $nw2, and $M,
$S, $E (each observed, perm, p_value); $E also carries
edge_names, a from/to data frame aligned to the per-edge vector.
Examples
set.seed(1)
a <- matrix(stats::rnorm(150 * 5), 150, 5)
b <- matrix(stats::rnorm(150 * 5), 150, 5)
colnames(a) <- colnames(b) <- paste0("V", 1:5)
fit <- net_compare(a, b, iter = 25)
fit
#> Network Comparison Test (25 permutations)
#> Global strength (M): observed 0.000, p = 0.423
#> Network structure (S): observed 0.000, p = 0.423