Print Permutation Test Results
Usage
# S3 method for class 'group_tna_permutation'
print(x, ...)Arguments
- x
A
group_tna_permutationobject.- ...
Arguments passed to
print.tna_permutation().
See also
Validation functions
bootstrap(),
deprune(),
estimate_cs(),
permutation_test(),
permutation_test.group_tna(),
plot.group_tna_bootstrap(),
plot.group_tna_permutation(),
plot.group_tna_stability(),
plot.tna_bootstrap(),
plot.tna_permutation(),
plot.tna_reliability(),
plot.tna_stability(),
print.group_tna_bootstrap(),
print.group_tna_stability(),
print.summary.group_tna_bootstrap(),
print.summary.tna_bootstrap(),
print.tna_bootstrap(),
print.tna_clustering(),
print.tna_permutation(),
print.tna_reliability(),
print.tna_stability(),
prune(),
pruning_details(),
reliability(),
reprune(),
summary.group_tna_bootstrap(),
summary.tna_bootstrap()
Examples
model <- group_model(engagement_mmm)
# Small number of iterations for CRAN
perm <- permutation_test(model, iter = 20)
print(perm)
#> Cluster 1 vs. Cluster 2 :
#> # A tibble: 9 × 4
#> edge_name diff_true effect_size p_value
#> <chr> <dbl> <dbl> <dbl>
#> 1 Active -> Active 0.0189 0.683 0.524
#> 2 Average -> Active 0.220 3.57 0.0476
#> 3 Disengaged -> Active -0.108 -5.26 0.0476
#> 4 Active -> Average -0.0699 -3.21 0.0476
#> 5 Average -> Average -0.0875 -1.51 0.286
#> 6 Disengaged -> Average -0.349 -7.65 0.0476
#> 7 Active -> Disengaged 0.0509 2.83 0.0476
#> 8 Average -> Disengaged -0.132 -3.10 0.0476
#> 9 Disengaged -> Disengaged 0.457 8.19 0.0476
#>
#> Cluster 1 vs. Cluster 3 :
#> # A tibble: 9 × 4
#> edge_name diff_true effect_size p_value
#> <chr> <dbl> <dbl> <dbl>
#> 1 Active -> Active 0.277 6.57 0.0476
#> 2 Average -> Active 0.159 1.42 0.190
#> 3 Disengaged -> Active 0.0479 1.20 0.333
#> 4 Active -> Average -0.0358 -1.01 0.476
#> 5 Average -> Average -0.277 -2.50 0.0476
#> 6 Disengaged -> Average -0.438 -6.40 0.0476
#> 7 Active -> Disengaged -0.241 -8.38 0.0476
#> 8 Average -> Disengaged 0.118 1.16 0.286
#> 9 Disengaged -> Disengaged 0.390 6.29 0.0476
#>
#> Cluster 2 vs. Cluster 3 :
#> # A tibble: 9 × 4
#> edge_name diff_true effect_size p_value
#> <chr> <dbl> <dbl> <dbl>
#> 1 Active -> Active 0.258 3.72 0.0476
#> 2 Average -> Active -0.0602 -1.11 0.381
#> 3 Disengaged -> Active 0.156 1.38 0.333
#> 4 Active -> Average 0.0341 1.19 0.333
#> 5 Average -> Average -0.190 -2.07 0.0952
#> 6 Disengaged -> Average -0.0889 -0.660 0.571
#> 7 Active -> Disengaged -0.292 -4.90 0.0476
#> 8 Average -> Disengaged 0.25 2.61 0.0476
#> 9 Disengaged -> Disengaged -0.0667 -0.636 0.476
#>