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 0.666 0.619
#> 2 Average -> Active 0.220 3.09 0.0476
#> 3 Disengaged -> Active -0.108 -4.80 0.0476
#> 4 Active -> Average -0.0699 -2.86 0.0476
#> 5 Average -> Average -0.0875 -1.24 0.190
#> 6 Disengaged -> Average -0.349 -7.20 0.0476
#> 7 Active -> Disengaged 0.0509 2.60 0.0476
#> 8 Average -> Disengaged -0.132 -2.58 0.0476
#> 9 Disengaged -> Disengaged 0.457 9.37 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 5.79 0.0476
#> 2 Average -> Active 0.159 1.79 0.0952
#> 3 Disengaged -> Active 0.0479 1.34 0.286
#> 4 Active -> Average -0.0358 -0.699 0.524
#> 5 Average -> Average -0.277 -3.34 0.0476
#> 6 Disengaged -> Average -0.438 -6.04 0.0476
#> 7 Active -> Disengaged -0.241 -8.81 0.0476
#> 8 Average -> Disengaged 0.118 1.86 0.0952
#> 9 Disengaged -> Disengaged 0.390 4.77 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 3.64 0.0476
#> 2 Average -> Active -0.0602 -1.31 0.238
#> 3 Disengaged -> Active 0.156 2.18 0.0476
#> 4 Active -> Average 0.0341 0.990 0.333
#> 5 Average -> Average -0.190 -2.08 0.143
#> 6 Disengaged -> Average -0.0889 -0.898 0.333
#> 7 Active -> Disengaged -0.292 -5.77 0.0476
#> 8 Average -> Disengaged 0.25 2.64 0.0476
#> 9 Disengaged -> Disengaged -0.0667 -0.683 0.476
#>