Print Permutation Test Results

Print Permutation Test Results

Usage

# S3 method for class 'group_tna_permutation'
print(x, ...)

Arguments

x

A group_tna_permutation object.

...

Arguments passed to print.tna_permutation().

Value

x (invisibly).

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_stability(), print.group_tna_bootstrap(), print.group_tna_stability(), print.summary.group_tna_bootstrap(), print.summary.tna_bootstrap(), print.tna_bootstrap(), print.tna_permutation(), print.tna_stability(), prune(), pruning_details(), 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            0.214         5.62  0.0476
#> 2 Average -> Active           0.188         3.59  0.0476
#> 3 Disengaged -> Active        0             0     1     
#> 4 Active -> Average          -0.148        -4.41  0.0476
#> 5 Average -> Average         -0.126        -2.63  0.0476
#> 6 Disengaged -> Average      -0.192        -1.97  0.0476
#> 7 Active -> Disengaged       -0.0657       -5.04  0.0476
#> 8 Average -> Disengaged      -0.0622       -4.05  0.0476
#> 9 Disengaged -> Disengaged    0.192         2.13  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            0.405         7.03  0.0476
#> 2 Average -> Active           0.354        11.5   0.0476
#> 3 Disengaged -> Active        0.268        10.9   0.0476
#> 4 Active -> Average          -0.314        -5.85  0.0476
#> 5 Average -> Average         -0.113        -3.83  0.0476
#> 6 Disengaged -> Average      -0.0898       -1.79  0.0476
#> 7 Active -> Disengaged       -0.0912       -5.46  0.0476
#> 8 Average -> Disengaged      -0.241        -7.44  0.0476
#> 9 Disengaged -> Disengaged   -0.178        -3.08  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            0.192        4.82   0.0476
#> 2 Average -> Active           0.166        5.12   0.0476
#> 3 Disengaged -> Active        0.268        9.07   0.0476
#> 4 Active -> Average          -0.166       -3.09   0.0476
#> 5 Average -> Average          0.0129       0.470  0.667 
#> 6 Disengaged -> Average       0.103        3.05   0.0476
#> 7 Active -> Disengaged       -0.0256      -0.906  0.381 
#> 8 Average -> Disengaged      -0.178       -5.38   0.0476
#> 9 Disengaged -> Disengaged   -0.370       -9.15   0.0476