Print group_tna Bootstrap Results
Usage
# S3 method for class 'group_tna_bootstrap'
print(x, ...)Arguments
- x
A
group_tna_bootstrapobject.- ...
Arguments passed to
print.tna_bootstrap().
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_permutation(),
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)
# Low number of iteration for CRAN
boot <- bootstrap(model, iter = 10)
print(boot)
#> Cluster 1 :
#> Non-significant Edges
#>
#> from to weight p_value cr_lower cr_upper ci_lower
#> 1 Disengaged Disengaged 0.68079470 0.09090909 0.51059603 0.85099338 0.6657594
#> 2 Engaged Disengaged 0.02027027 0.18181818 0.01520270 0.02533784 0.0161201
#> 3 Moderate Disengaged 0.12065157 0.09090909 0.09048868 0.15081447 0.1137906
#> 4 Disengaged Engaged 0.15827815 0.09090909 0.11870861 0.19784768 0.1476810
#> 5 Engaged Engaged 0.66164241 0.09090909 0.49623181 0.82705301 0.6368803
#> 6 Moderate Engaged 0.12424075 0.09090909 0.09318056 0.15530094 0.1179372
#> 7 Disengaged Moderate 0.16092715 0.09090909 0.12069536 0.20115894 0.1399645
#> 8 Engaged Moderate 0.31808732 0.09090909 0.23856549 0.39760915 0.3061670
#> 9 Moderate Moderate 0.75510768 0.09090909 0.56633076 0.94388459 0.7449449
#> ci_upper
#> 1 0.70943332
#> 2 0.02598361
#> 3 0.12702705
#> 4 0.16641885
#> 5 0.67644193
#> 6 0.13249769
#> 7 0.16813406
#> 8 0.34293374
#> 9 0.76631630
#>
#> Cluster 2 :
#> Non-significant Edges
#>
#> from to weight p_value cr_lower cr_upper
#> 1 Disengaged Disengaged 0.911206588 0.09090909 0.6834049409 1.139008235
#> 2 Engaged Disengaged 0.308310992 0.09090909 0.2312332440 0.385388740
#> 3 Moderate Disengaged 0.118299445 0.18181818 0.0887245841 0.147874307
#> 4 Disengaged Engaged 0.087719298 0.09090909 0.0657894737 0.109649123
#> 5 Engaged Engaged 0.671581769 0.09090909 0.5036863271 0.839477212
#> 6 Moderate Engaged 0.053604436 0.27272727 0.0402033272 0.067005545
#> 7 Disengaged Moderate 0.001074114 0.54545455 0.0008055854 0.001342642
#> 8 Engaged Moderate 0.020107239 0.09090909 0.0150804290 0.025134048
#> 9 Moderate Moderate 0.828096118 0.09090909 0.6210720887 1.035120148
#> ci_lower ci_upper
#> 1 0.9042475542 0.915694489
#> 2 0.2908307395 0.352150624
#> 3 0.1109525079 0.155099471
#> 4 0.0835661675 0.094376263
#> 5 0.6311603093 0.691186399
#> 6 0.0397631448 0.072690593
#> 7 0.0003506053 0.002301128
#> 8 0.0166890670 0.024027954
#> 9 0.7956625683 0.832094471
#>
#> Cluster 3 :
#> Non-significant Edges
#>
#> from to weight p_value cr_lower cr_upper ci_lower
#> 1 Disengaged Disengaged 0.87538657 0.09090909 0.65653993 1.09423322 0.87088736
#> 2 Engaged Disengaged 0.06246451 0.09090909 0.04684838 0.07808064 0.05345745
#> 3 Moderate Disengaged 0.18153446 0.09090909 0.13615085 0.22691808 0.17157098
#> 4 Disengaged Engaged 0.11115154 0.09090909 0.08336365 0.13893942 0.10568490
#> 5 Engaged Engaged 0.66524702 0.09090909 0.49893526 0.83155877 0.65613942
#> 6 Moderate Engaged 0.14980494 0.09090909 0.11235371 0.18725618 0.13929035
#> 7 Disengaged Moderate 0.01346189 0.09090909 0.01009642 0.01682736 0.01151166
#> 8 Engaged Moderate 0.27228847 0.09090909 0.20421635 0.34036059 0.25850123
#> 9 Moderate Moderate 0.66866060 0.09090909 0.50149545 0.83582575 0.65728392
#> ci_upper
#> 1 0.88041944
#> 2 0.06720318
#> 3 0.18886737
#> 4 0.11586137
#> 5 0.67874296
#> 6 0.16139783
#> 7 0.01452551
#> 8 0.28488240
#> 9 0.67961316
#>