Print a Bootstrap Summary
Usage
# S3 method for class 'summary.tna_bootstrap'
print(x, ...)Value
A summary.tna_bootstrap object (invisibly) containing the weight,
estimated p-value and confidence interval of each edge.
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_permutation(),
print.group_tna_stability(),
print.summary.group_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 <- tna(group_regulation)
# Small number of iterations for CRAN
boot <- bootstrap(model, iter = 10)
print(summary(boot))
#> from to weight p_value sig cr_lower cr_upper
#> 2 cohesion adapt 0.0029498525 0.72727273 FALSE 0.0022123894 0.003687316
#> 3 consensus adapt 0.0047400853 0.18181818 FALSE 0.0035550640 0.005925107
#> 4 coregulate adapt 0.0162436548 0.27272727 FALSE 0.0121827411 0.020304569
#> 5 discuss adapt 0.0713743356 0.09090909 FALSE 0.0535307517 0.089217920
#> 6 emotion adapt 0.0024673951 0.54545455 FALSE 0.0018505464 0.003084244
#> 7 monitor adapt 0.0111653873 0.27272727 FALSE 0.0083740405 0.013956734
#> 8 plan adapt 0.0009745006 0.63636364 FALSE 0.0007308754 0.001218126
#> 9 synthesis adapt 0.2346625767 0.09090909 FALSE 0.1759969325 0.293328221
#> 10 adapt cohesion 0.2730844794 0.09090909 FALSE 0.2048133595 0.341355599
#> 11 cohesion cohesion 0.0271386431 0.27272727 FALSE 0.0203539823 0.033923304
#> 12 consensus cohesion 0.0148522673 0.18181818 FALSE 0.0111392005 0.018565334
#> 13 coregulate cohesion 0.0360406091 0.18181818 FALSE 0.0270304569 0.045050761
#> 14 discuss cohesion 0.0475828904 0.09090909 FALSE 0.0356871678 0.059478613
#> 15 emotion cohesion 0.3253436729 0.09090909 FALSE 0.2440077547 0.406679591
#> 16 monitor cohesion 0.0558269365 0.09090909 FALSE 0.0418702024 0.069783671
#> 17 plan cohesion 0.0251745980 0.18181818 FALSE 0.0188809485 0.031468248
#> 18 synthesis cohesion 0.0337423313 0.18181818 FALSE 0.0253067485 0.042177914
#> 19 adapt consensus 0.4774066798 0.09090909 FALSE 0.3580550098 0.596758350
#> 20 cohesion consensus 0.4979351032 0.09090909 FALSE 0.3734513274 0.622418879
#> 21 consensus consensus 0.0820034761 0.09090909 FALSE 0.0615026070 0.102504345
#> 22 coregulate consensus 0.1345177665 0.09090909 FALSE 0.1008883249 0.168147208
#> 23 discuss consensus 0.3211845103 0.09090909 FALSE 0.2408883827 0.401480638
#> 24 emotion consensus 0.3204088826 0.09090909 FALSE 0.2403066620 0.400511103
#> 25 monitor consensus 0.1591067690 0.09090909 FALSE 0.1193300768 0.198883461
#> 26 plan consensus 0.2904011694 0.09090909 FALSE 0.2178008771 0.363001462
#> 27 synthesis consensus 0.4662576687 0.09090909 FALSE 0.3496932515 0.582822086
#> 28 adapt coregulate 0.0216110020 0.54545455 FALSE 0.0162082515 0.027013752
#> 29 cohesion coregulate 0.1191740413 0.09090909 FALSE 0.0893805310 0.148967552
#> 30 consensus coregulate 0.1877073787 0.09090909 FALSE 0.1407805340 0.234634223
#> 31 coregulate coregulate 0.0233502538 0.18181818 FALSE 0.0175126904 0.029187817
#> 32 discuss coregulate 0.0842824601 0.09090909 FALSE 0.0632118451 0.105353075
#> 33 emotion coregulate 0.0341910469 0.18181818 FALSE 0.0256432852 0.042738809
#> 34 monitor coregulate 0.0579204466 0.09090909 FALSE 0.0434403350 0.072400558
#> 35 plan coregulate 0.0172161767 0.09090909 FALSE 0.0129121325 0.021520221
#> 36 synthesis coregulate 0.0444785276 0.09090909 FALSE 0.0333588957 0.055598160
#> 37 adapt discuss 0.0589390963 0.09090909 FALSE 0.0442043222 0.073673870
#> 38 cohesion discuss 0.0595870206 0.09090909 FALSE 0.0446902655 0.074483776
#> 39 consensus discuss 0.1880233844 0.09090909 FALSE 0.1410175383 0.235029231
#> 40 coregulate discuss 0.2736040609 0.09090909 FALSE 0.2052030457 0.342005076
#> 41 discuss discuss 0.1948873703 0.09090909 FALSE 0.1461655277 0.243609213
#> 42 emotion discuss 0.1018681706 0.09090909 FALSE 0.0764011280 0.127335213
#> 43 monitor discuss 0.3754361479 0.09090909 FALSE 0.2815771110 0.469295185
#> 44 plan discuss 0.0678902063 0.09090909 FALSE 0.0509176547 0.084862758
#> 45 synthesis discuss 0.0628834356 0.27272727 FALSE 0.0471625767 0.078604294
#> 46 adapt emotion 0.1198428291 0.18181818 FALSE 0.0898821218 0.149803536
#> 47 cohesion emotion 0.1156342183 0.09090909 FALSE 0.0867256637 0.144542773
#> 48 consensus emotion 0.0726813083 0.09090909 FALSE 0.0545109812 0.090851635
#> 49 coregulate emotion 0.1720812183 0.09090909 FALSE 0.1290609137 0.215101523
#> 50 discuss emotion 0.1057960010 0.09090909 FALSE 0.0793470008 0.132245001
#> 51 emotion emotion 0.0768417342 0.09090909 FALSE 0.0576313007 0.096052168
#> 52 monitor emotion 0.0907187718 0.09090909 FALSE 0.0680390789 0.113398465
#> 53 plan emotion 0.1468247523 0.09090909 FALSE 0.1101185642 0.183530940
#> 54 synthesis emotion 0.0705521472 0.09090909 FALSE 0.0529141104 0.088190184
#> 55 adapt monitor 0.0333988212 0.18181818 FALSE 0.0250491159 0.041748527
#> 56 cohesion monitor 0.0330383481 0.18181818 FALSE 0.0247787611 0.041297935
#> 57 consensus monitor 0.0466108390 0.09090909 FALSE 0.0349581292 0.058263549
#> 58 coregulate monitor 0.0862944162 0.09090909 FALSE 0.0647208122 0.107868020
#> 59 discuss monitor 0.0222728423 0.09090909 FALSE 0.0167046317 0.027841053
#> 60 emotion monitor 0.0363059570 0.09090909 FALSE 0.0272294677 0.045382446
#> 61 monitor monitor 0.0181437544 0.36363636 FALSE 0.0136078158 0.022679693
#> 62 plan monitor 0.0755237941 0.09090909 FALSE 0.0566428455 0.094404743
#> 63 synthesis monitor 0.0122699387 0.45454545 FALSE 0.0092024540 0.015337423
#> 64 adapt plan 0.0157170923 0.54545455 FALSE 0.0117878193 0.019646365
#> 65 cohesion plan 0.1410029499 0.09090909 FALSE 0.1057522124 0.176253687
#> 66 consensus plan 0.3957971243 0.09090909 FALSE 0.2968478433 0.494746405
#> 67 coregulate plan 0.2390862944 0.09090909 FALSE 0.1793147208 0.298857868
#> 68 discuss plan 0.0116426221 0.18181818 FALSE 0.0087319666 0.014553278
#> 69 emotion plan 0.0997532605 0.09090909 FALSE 0.0748149454 0.124691576
#> 70 monitor plan 0.2156315422 0.09090909 FALSE 0.1617236567 0.269539428
#> 71 plan plan 0.3742082183 0.09090909 FALSE 0.2806561637 0.467760273
#> 72 synthesis plan 0.0751533742 0.09090909 FALSE 0.0563650307 0.093941718
#> 74 cohesion synthesis 0.0035398230 0.27272727 FALSE 0.0026548673 0.004424779
#> 75 consensus synthesis 0.0075841365 0.09090909 FALSE 0.0056881024 0.009480171
#> 76 coregulate synthesis 0.0187817259 0.45454545 FALSE 0.0140862944 0.023477157
#> 77 discuss synthesis 0.1409769679 0.09090909 FALSE 0.1057327259 0.176221210
#> 78 emotion synthesis 0.0028198802 0.81818182 FALSE 0.0021149101 0.003524850
#> 79 monitor synthesis 0.0160502442 0.36363636 FALSE 0.0120376832 0.020062805
#> 80 plan synthesis 0.0017865844 0.54545455 FALSE 0.0013399383 0.002233230
#> ci_lower ci_upper
#> 2 0.0007130671 0.005546641
#> 3 0.0038056497 0.006099700
#> 4 0.0107008173 0.020422358
#> 5 0.0650743121 0.075987842
#> 6 0.0012486068 0.003773311
#> 7 0.0086203067 0.015664861
#> 8 0.0003934947 0.001683347
#> 9 0.2238691678 0.264251251
#> 10 0.2522127815 0.295128143
#> 11 0.0201281360 0.033778140
#> 12 0.0129370881 0.018303202
#> 13 0.0283431075 0.043739348
#> 14 0.0432608220 0.053088956
#> 15 0.3082364203 0.337365020
#> 16 0.0457503285 0.059714754
#> 17 0.0211668526 0.030965604
#> 18 0.0264332380 0.044140735
#> 19 0.4199392539 0.505797444
#> 20 0.4847321591 0.521411126
#> 21 0.0775865221 0.087810633
#> 22 0.1187609341 0.143728233
#> 23 0.3148761620 0.335012162
#> 24 0.3044894401 0.348797392
#> 25 0.1523010777 0.170679063
#> 26 0.2826120460 0.300308455
#> 27 0.4437992642 0.486597179
#> 28 0.0146089133 0.030688818
#> 29 0.1008848036 0.134445035
#> 30 0.1815634263 0.198870204
#> 31 0.0197777659 0.029037562
#> 32 0.0794434140 0.088321046
#> 33 0.0241140261 0.038864056
#> 34 0.0484880188 0.066578209
#> 35 0.0159161382 0.019673810
#> 36 0.0359701738 0.051739620
#> 37 0.0460550809 0.062648975
#> 38 0.0485445286 0.060586887
#> 39 0.1833960253 0.194680126
#> 40 0.2508040320 0.275828026
#> 41 0.1851221508 0.201617275
#> 42 0.0876096720 0.107075441
#> 43 0.3583696315 0.391820009
#> 44 0.0631460990 0.073845676
#> 45 0.0494793824 0.083559435
#> 46 0.1022468635 0.150227117
#> 47 0.0981826498 0.121785326
#> 48 0.0659664819 0.077753011
#> 49 0.1569070752 0.186397713
#> 50 0.0956807373 0.108518077
#> 51 0.0668721195 0.084925190
#> 52 0.0757758818 0.097952209
#> 53 0.1377310773 0.152132755
#> 54 0.0544584479 0.083444421
#> 55 0.0284533524 0.045478250
#> 56 0.0264596763 0.042770044
#> 57 0.0453945028 0.048793583
#> 58 0.0765270664 0.099825842
#> 59 0.0196961405 0.023974786
#> 60 0.0317423700 0.041061780
#> 61 0.0119302928 0.024706749
#> 62 0.0705167630 0.081076656
#> 63 0.0055452171 0.019418608
#> 64 0.0061176498 0.028324385
#> 65 0.1222279512 0.161793540
#> 66 0.3860539654 0.402548672
#> 67 0.2281564559 0.262409323
#> 68 0.0088198850 0.013565788
#> 69 0.0971410295 0.111054828
#> 70 0.1994817354 0.237846677
#> 71 0.3657373995 0.379954945
#> 72 0.0602245188 0.087150977
#> 74 0.0020127997 0.005063406
#> 75 0.0058930351 0.008618270
#> 76 0.0148550662 0.026216965
#> 77 0.1325273675 0.149146980
#> 78 0.0012559920 0.003933167
#> 79 0.0099911318 0.020725421
#> 80 0.0011307321 0.002679089