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Mediator-pass through with normal errors

Usage

model_outcome_t(mediator, beta_w = NULL, beta_x = NULL, df = 5)

Arguments

mediator

TODO

beta_w

TODO

beta_x

TODO

df

TODO

Value

TODO

Examples


m <- model_mediator_informative(n = 100, k = 5)
o <- model_outcome_normal(m)

o
#> $y
#>   [1]  6.885794887  8.616529330  8.309806448  7.679211539  7.684468516
#>   [6]  7.337078038  5.398795158  5.507178971  8.476648320  7.517168436
#>  [11]  6.694188050  4.343510677  4.558102978  3.507938086  5.693456181
#>  [16]  3.490741314  3.212255045  4.526540048  6.528682086  5.259790138
#>  [21]  8.959429610 10.236259642  7.880375283  9.589704459  7.258357286
#>  [26]  6.048705771  7.440302874  6.043156644  6.717170023  5.177781084
#>  [31]  4.827437890  5.645973500  5.188371471  5.943550083  5.275006715
#>  [36]  5.868817401  3.173128065  2.735345307  2.640242868  6.039791393
#>  [41]  4.837939895  4.182220529 -1.453787485 -0.835306283 -1.212255177
#>  [46] -0.001592763  0.080785913 -1.889238920  0.088798822 -1.424897926
#>  [51] -1.695219493 -3.331646732 -0.217126873 -2.331063914 -1.004994749
#>  [56]  2.577802905  2.801285697  2.702781381  1.875323797  0.906356874
#>  [61]  3.837462179  4.388799809 -1.442626645  0.410720148 -0.741127284
#>  [66] -2.162556794 -1.146493847 -1.319977965  0.319086429 -1.275552498
#>  [71]  0.154968156  0.478343508 -1.038708298 -1.324986066 -0.038292777
#>  [76] -0.536963642  1.795297306  1.706818238  1.729636891  5.243369009
#>  [81]  4.155037863  5.010355715  4.007741564  3.279821667  4.293295353
#>  [86]  4.798691138  3.249207933  3.121136986  5.302218611  4.456553286
#>  [91]  2.305541547  1.689279795  2.653248191  2.432678719  2.835898869
#>  [96]  3.752631868  1.919379262  2.567495297  2.121121784  1.325709916
#> 
#> $beta_w
#>       C1       C2       C3       C4       C5 
#> 1.642215 1.778847 1.225735 1.736604 1.176901 
#> 
#> $beta_x
#>       US1       US2       US3       US4       US5 
#> 0.8888388 0.7109887 1.0899153 0.7026465 1.5884116 
#> 
#> $mediator
#> $n
#> [1] 100
#> 
#> $k
#> [1] 5
#> 
#> $X
#>              US1        US2         US3         US4         US5
#>   [1,] 0.3606659 -0.7408713  0.16843208  3.49777411  0.48888510
#>   [2,] 0.3601276 -0.7397656  0.16818071  3.49255395  0.48815548
#>   [3,] 0.3563370 -0.7319790  0.16641047  3.45579198  0.48301724
#>   [4,] 0.3430270 -0.7046380  0.16019468  3.32671072  0.46497551
#>   [5,] 0.3429907 -0.7045635  0.16017774  3.32635887  0.46492633
#>   [6,] 0.3226094 -0.6626966  0.15065960  3.12869888  0.43729933
#>   [7,] 0.3149597 -0.6469828  0.14708716  3.05451111  0.42693008
#>   [8,] 0.2922543 -0.6003419  0.13648367  2.83431189  0.39615276
#>   [9,] 0.2818362 -0.5789413  0.13161839  2.73327618  0.38203096
#>  [10,] 0.2562530 -0.5263889  0.11967096  2.48516785  0.34735277
#>  [11,] 0.2322189 -0.4770186  0.10844696  2.25208264  0.31477437
#>  [12,] 0.2302930 -0.4730625  0.10754756  2.23340522  0.31216382
#>  [13,] 0.2077472 -0.4267495  0.09701860  2.01475373  0.28160283
#>  [14,] 0.2053569 -0.4218393  0.09590232  1.99157223  0.27836274
#>  [15,] 0.2012248 -0.4133512  0.09397259  1.95149816  0.27276158
#>  [16,] 0.1623482 -0.3334919  0.07581712  1.57446949  0.22006415
#>  [17,] 0.1495477 -0.3071973  0.06983922  1.45032833  0.20271289
#>  [18,] 3.6233461  0.7488110 -0.08831216 -0.17902929  0.11714477
#>  [19,] 3.5647848  0.7367086 -0.08688484 -0.17613578  0.11525146
#>  [20,] 3.4332846  0.7095324 -0.08367978 -0.16963836  0.11099998
#>  [21,] 3.3680776  0.6960565 -0.08209048 -0.16641649  0.10889180
#>  [22,] 3.2222496  0.6659193 -0.07853620 -0.15921114  0.10417710
#>  [23,] 3.1645185  0.6539884 -0.07712911 -0.15635865  0.10231063
#>  [24,] 3.0966080  0.6399538 -0.07547393 -0.15300320  0.10011504
#>  [25,] 2.9183339  0.6031112 -0.07112883 -0.14419468  0.09435134
#>  [26,] 2.7061386  0.5592583 -0.06595698 -0.13371013  0.08749095
#>  [27,] 2.5167777  0.5201244 -0.06134167 -0.12435382  0.08136881
#>  [28,] 2.4698035  0.5104166 -0.06019676 -0.12203283  0.07985011
#>  [29,] 2.4429188  0.5048606 -0.05954150 -0.12070446  0.07898091
#>  [30,] 2.1817634  0.4508894 -0.05317633 -0.10780078  0.07053761
#>  [31,] 2.1095545  0.4359665 -0.05141637 -0.10423295  0.06820306
#>  [32,] 2.0587833  0.4254740 -0.05017892 -0.10172434  0.06656160
#>  [33,] 2.0030094  0.4139476 -0.04881954 -0.09896856  0.06475840
#>  [34,] 1.9091415  0.3945486 -0.04653169 -0.09433055  0.06172360
#>  [35,] 1.7662392  0.3650160 -0.04304872 -0.08726976  0.05710348
#>  [36,] 1.6518039  0.3413665 -0.04025957 -0.08161552  0.05340373
#>  [37,] 1.6097805  0.3326818 -0.03923533 -0.07953915  0.05204509
#>  [38,] 1.6038694  0.3314602 -0.03909126 -0.07924708  0.05185398
#>  [39,] 1.5791585  0.3263534 -0.03848898 -0.07802612  0.05105507
#>  [40,] 1.5061432  0.3112638 -0.03670937 -0.07441843  0.04869444
#>  [41,] 1.3990726  0.2891363 -0.03409973 -0.06912808  0.04523279
#>  [42,] 1.2909640  0.2667943 -0.03146479 -0.06378645  0.04173758
#>  [43,] 0.5519504 -2.8697247 -2.24587239 -0.54023437  0.22928885
#>  [44,] 0.5424363 -2.8202583 -2.20715948 -0.53092216  0.22533651
#>  [45,] 0.4982832 -2.5906955 -2.02750162 -0.48770628  0.20699462
#>  [46,] 0.4966379 -2.5821415 -2.02080718 -0.48609596  0.20631116
#>  [47,] 0.4847011 -2.5200792 -1.97223668 -0.47441255  0.20135243
#>  [48,] 0.4499579 -2.3394406 -1.83086728 -0.44040678  0.18691955
#>  [49,] 0.4418514 -2.2972930 -1.79788217 -0.43247236  0.18355198
#>  [50,] 0.4388311 -2.2815896 -1.78559257 -0.42951616  0.18229729
#>  [51,] 0.4354579 -2.2640515 -1.77186709 -0.42621455  0.18089601
#>  [52,] 0.4311918 -2.2418710 -1.75450844 -0.42203901  0.17912381
#>  [53,] 0.3912259 -2.0340789 -1.59188843 -0.38292151  0.16252137
#>  [54,] 0.3791887 -1.9714945 -1.54290930 -0.37113980  0.15752092
#>  [55,] 0.3620831 -1.8825585 -1.47330722 -0.35439734  0.15041501
#>  [56,] 0.3114915 -1.6195203 -1.26745114 -0.30487960  0.12939845
#>  [57,] 0.2945485 -1.5314297 -1.19851063 -0.28829627  0.12236008
#>  [58,] 0.2675086 -1.3908424 -1.08848578 -0.26183030  0.11112726
#>  [59,] 0.2588835 -1.3459985 -1.05339055 -0.25338830  0.10754427
#>  [60,] 0.2108691 -1.0963599 -0.85802115 -0.20639308  0.08759833
#>  [61,] 0.2017461 -1.0489270 -0.82089972 -0.19746369  0.08380848
#>  [62,] 0.1918022 -0.9972264 -0.78043832 -0.18773088  0.07967764
#>  [63,] 0.2803225 -0.4445919  0.08478710  0.42993655 -3.64180913
#>  [64,] 0.2792748 -0.4429303  0.08447022  0.42832968 -3.62819805
#>  [65,] 0.2713862 -0.4304189  0.08208419  0.41623071 -3.52571277
#>  [66,] 0.2671326 -0.4236726  0.08079763  0.40970681 -3.47045162
#>  [67,] 0.2605326 -0.4132050  0.07880138  0.39958428 -3.38470803
#>  [68,] 0.2564138 -0.4066726  0.07755560  0.39326719 -3.33119863
#>  [69,] 0.2062586 -0.3271264  0.06238553  0.31634314 -2.67960780
#>  [70,] 0.1941238 -0.3078806  0.05871521  0.29773176 -2.52195873
#>  [71,] 0.1924839 -0.3052798  0.05821921  0.29521666 -2.50065440
#>  [72,] 0.1872239 -0.2969373  0.05662823  0.28714917 -2.43231816
#>  [73,] 0.1697415 -0.2692102  0.05134047  0.26033610 -2.20519606
#>  [74,] 0.1620913 -0.2570770  0.04902657  0.24860282 -2.10580849
#>  [75,] 0.1564302 -0.2480985  0.04731430  0.23992030 -2.03226250
#>  [76,] 0.1332909 -0.2113995  0.04031552  0.20443104 -1.73164811
#>  [77,] 0.1253609 -0.1988225  0.03791699  0.19226861 -1.62862540
#>  [78,] 0.1142560 -0.1812102  0.03455819  0.17523689 -1.48435695
#>  [79,] 0.1060242 -0.1681545  0.03206835  0.16261148 -1.37741245
#>  [80,] 0.5214114 -2.1331704  2.95377060 -0.63377768  0.24689386
#>  [81,] 0.5195248 -2.1254519  2.94308283 -0.63148446  0.24600052
#>  [82,] 0.4987947 -2.0406420  2.82564777 -0.60628693  0.23618459
#>  [83,] 0.4550182 -1.8615461  2.57765623 -0.55307646  0.21545597
#>  [84,] 0.4481604 -1.8334896  2.53880689 -0.54474073  0.21220871
#>  [85,] 0.4348531 -1.7790478  2.46342206 -0.52856573  0.20590759
#>  [86,] 0.4244968 -1.7366787  2.40475412 -0.51597761  0.20100377
#>  [87,] 0.3925668 -1.6060483  2.22387205 -0.47716653  0.18588456
#>  [88,] 0.3921958 -1.6045305  2.22177042 -0.47671560  0.18570890
#>  [89,] 0.3419448 -1.3989463  1.93710098 -0.41563531  0.16191452
#>  [90,] 0.3358935 -1.3741895  1.90282061 -0.40827993  0.15904916
#>  [91,] 0.3227413 -1.3203820  1.82831403 -0.39229337  0.15282145
#>  [92,] 0.3003012 -1.2285762  1.70119196 -0.36501734  0.14219583
#>  [93,] 0.2868265 -1.1734492  1.62485829 -0.34863876  0.13581540
#>  [94,] 0.2867399 -1.1730951  1.62436796 -0.34853355  0.13577442
#>  [95,] 0.2765020 -1.1312101  1.56637052 -0.33608929  0.13092664
#>  [96,] 0.2361601 -0.9661656  1.33783565 -0.28705356  0.11182433
#>  [97,] 0.2353125 -0.9626979  1.33303397 -0.28602329  0.11142297
#>  [98,] 0.2276743 -0.9314488  1.28976387 -0.27673901  0.10780620
#>  [99,] 0.2047953 -0.8378474  1.16015531 -0.24892947  0.09697274
#> [100,] 0.2033402 -0.8318946  1.15191257 -0.24716086  0.09628376
#> 
#> $W
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>           C1       C2       C3       C4       C5
#> 20  2.930756 .        .        .        .       
#> 1   2.870189 .        .        .        .       
#> 8   2.865905 .        .        .        .       
#> 17  2.835739 .        .        .        .       
#> 12  2.729818 .        .        .        .       
#> 15  2.729529 .        .        .        .       
#> 10  2.567334 .        .        .        .       
#> 16  2.506458 .        .        .        .       
#> 3   2.325768 .        .        .        .       
#> 6   2.242860 .        .        .        .       
#> 11  2.039268 .        .        .        .       
#> 5   1.848004 .        .        .        .       
#> 4   1.832678 .        .        .        .       
#> 14  1.653258 .        .        .        .       
#> 2   1.634236 .        .        .        .       
#> 9   1.601352 .        .        .        .       
#> 19  1.428629 .        .        .        .       
#> 7   1.291971 .        .        .        .       
#> 18  1.277308 .        .        .        .       
#> 13  1.190104 .        .        .        .       
#> 34  .        2.883388 .        .        .       
#> 30  .        2.777024 .        .        .       
#> 25  .        2.724281 .        .        .       
#> 22  .        2.606328 .        .        .       
#> 23  .        2.559632 .        .        .       
#> 31  .        2.504702 .        .        .       
#> 35  .        2.188869 .        .        .       
#> 27  .        2.035704 .        .        .       
#> 33  .        1.997709 .        .        .       
#> 26  .        1.975963 .        .        .       
#> 29  .        1.764727 .        .        .       
#> 36  .        1.706320 .        .        .       
#> 21  .        1.665254 .        .        .       
#> 32  .        1.620141 .        .        .       
#> 28  .        1.544216 .        .        .       
#> 37  .        1.336067 .        .        .       
#> 38  .        1.302076 .        .        .       
#> 24  .        1.297295 .        .        .       
#> 39  .        1.044201 .        .        .       
#> 51  .        .        2.654786 .        .       
#> 50  .        .        2.590977 .        .       
#> 52  .        .        2.405257 .        .       
#> 49  .        .        2.361923 .        .       
#> 40  .        .        2.360504 .        .       
#> 47  .        .        2.327747 .        .       
#> 43  .        .        2.304942 .        .       
#> 45  .        .        2.091304 .        .       
#> 54  .        .        1.665083 .        .       
#> 44  .        .        1.429971 .        .       
#> 46  .        .        1.383866 .        .       
#> 41  .        .        1.218249 .        .       
#> 42  .        .        1.131645 .        .       
#> 55  .        .        1.127204 .        .       
#> 48  .        .        1.078437 .        .       
#> 53  .        .        1.025282 .        .       
#> 56  .        .        .        2.950460 .       
#> 65  .        .        .        2.918540 .       
#> 61  .        .        .        2.899601 .       
#> 73  .        .        .        2.836101 .       
#> 75  .        .        .        2.791648 .       
#> 67  .        .        .        2.722676 .       
#> 66  .        .        .        2.679633 .       
#> 62  .        .        .        2.663580 .       
#> 60  .        .        .        2.345778 .       
#> 71  .        .        .        2.155490 .       
#> 69  .        .        .        2.028676 .       
#> 58  .        .        .        2.026959 .       
#> 68  .        .        .        1.956569 .       
#> 59  .        .        .        1.935521 .       
#> 76  .        .        .        1.693923 .       
#> 63  .        .        .        1.634762 .       
#> 57  .        .        .        1.574514 .       
#> 72  .        .        .        1.392946 .       
#> 74  .        .        .        1.310074 .       
#> 64  .        .        .        1.194024 .       
#> 70  .        .        .        1.107997 .       
#> 90  .        .        .        .        2.959062
#> 84  .        .        .        .        2.948355
#> 78  .        .        .        .        2.929489
#> 96  .        .        .        .        2.830710
#> 100 .        .        .        .        2.582274
#> 99  .        .        .        .        2.543355
#> 87  .        .        .        .        2.467835
#> 97  .        .        .        .        2.409062
#> 89  .        .        .        .        2.227856
#> 81  .        .        .        .        2.225751
#> 79  .        .        .        .        2.011539
#> 93  .        .        .        .        1.940571
#> 86  .        .        .        .        1.906229
#> 95  .        .        .        .        1.831589
#> 77  .        .        .        .        1.773871
#> 91  .        .        .        .        1.704240
#> 85  .        .        .        .        1.627769
#> 82  .        .        .        .        1.627278
#> 98  .        .        .        .        1.569177
#> 92  .        .        .        .        1.340232
#> 83  .        .        .        .        1.335422
#> 94  .        .        .        .        1.292074
#> 80  .        .        .        .        1.162234
#> 88  .        .        .        .        1.153976
#> 
#> $A_model
#> Undirected Factor Model
#> -----------------------
#> 
#> Nodes (n): 100
#> Rank (k): 5
#> 
#> X: 100 x 5 [dgCMatrix] 
#> S: 5 x 5 [dsyMatrix] 
#> 
#> Poisson edges: TRUE 
#> Allow self loops: TRUE 
#> 
#> Expected edges: 6954
#> Expected degree: 69.5
#> Expected density: 1.40489
#> $Theta
#>          US1        US2         US3         US4         US5
#> C1 0.2518171 -0.2066664  0.05009058  1.10296467  0.15955236
#> C2 1.1725096  0.2423142 -0.02857769 -0.05793362  0.03790788
#> C3 0.3548408 -0.8582769 -0.70566183 -0.17769148  0.07748992
#> C4 0.1026717 -0.3354236 -0.17774695  0.03746066 -0.69347888
#> C5 0.1505455 -0.5917289  0.80108473 -0.15645850 -0.05865314
#> 
#> $model_name
#> [1] "informative"
#> 
#> $C_true_model
#> Undirected Degree-Corrected Stochastic Blockmodel
#> -------------------------------------------------
#> 
#> Nodes (n): 100 (arranged by block)
#> Blocks (k): 5
#> 
#> Traditional DCSBM parameterization:
#> 
#> Block memberships (z): 100 [factor] 
#> Degree heterogeneity (theta): 100 [numeric] 
#> Block probabilities (pi): 5 [numeric] 
#> 
#> Factor model parameterization:
#> 
#> X: 100 x 5 [dgCMatrix] 
#> S: 5 x 5 [dsyMatrix] 
#> 
#> Poisson edges: TRUE 
#> Allow self loops: TRUE 
#> 
#> Expected edges: 6954
#> Expected degree: 69.5
#> Expected density: 1.40489
#> $C_obs_model
#> Undirected Degree-Corrected Stochastic Blockmodel
#> -------------------------------------------------
#> 
#> Nodes (n): 100 (arranged by block)
#> Blocks (k): 5
#> 
#> Traditional DCSBM parameterization:
#> 
#> Block memberships (z): 100 [factor] 
#> Degree heterogeneity (theta): 100 [numeric] 
#> Block probabilities (pi): 5 [numeric] 
#> 
#> Factor model parameterization:
#> 
#> X: 100 x 5 [dgCMatrix] 
#> S: 5 x 5 [dsyMatrix] 
#> 
#> Poisson edges: TRUE 
#> Allow self loops: TRUE 
#> 
#> Expected edges: 7052
#> Expected degree: 70.5
#> Expected density: 1.42459
#> $zC_true
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>           C1       C2       C3       C4       C5
#> 1   2.870189 .        .        .        .       
#> 8   2.865905 .        .        .        .       
#> 17  2.835739 .        .        .        .       
#> 12  2.729818 .        .        .        .       
#> 15  2.729529 .        .        .        .       
#> 10  2.567334 .        .        .        .       
#> 16  2.506458 .        .        .        .       
#> 3   2.325768 .        .        .        .       
#> 6   2.242860 .        .        .        .       
#> 11  2.039268 .        .        .        .       
#> 5   1.848004 .        .        .        .       
#> 4   1.832678 .        .        .        .       
#> 14  1.653258 .        .        .        .       
#> 2   1.634236 .        .        .        .       
#> 9   1.601352 .        .        .        .       
#> 7   1.291971 .        .        .        .       
#> 13  1.190104 .        .        .        .       
#> 20  .        2.930756 .        .        .       
#> 34  .        2.883388 .        .        .       
#> 30  .        2.777024 .        .        .       
#> 25  .        2.724281 .        .        .       
#> 22  .        2.606328 .        .        .       
#> 23  .        2.559632 .        .        .       
#> 31  .        2.504702 .        .        .       
#> 40  .        2.360504 .        .        .       
#> 35  .        2.188869 .        .        .       
#> 27  .        2.035704 .        .        .       
#> 33  .        1.997709 .        .        .       
#> 26  .        1.975963 .        .        .       
#> 29  .        1.764727 .        .        .       
#> 36  .        1.706320 .        .        .       
#> 21  .        1.665254 .        .        .       
#> 32  .        1.620141 .        .        .       
#> 28  .        1.544216 .        .        .       
#> 19  .        1.428629 .        .        .       
#> 37  .        1.336067 .        .        .       
#> 38  .        1.302076 .        .        .       
#> 24  .        1.297295 .        .        .       
#> 18  .        1.277308 .        .        .       
#> 41  .        1.218249 .        .        .       
#> 42  .        1.131645 .        .        .       
#> 39  .        1.044201 .        .        .       
#> 56  .        .        2.950460 .        .       
#> 61  .        .        2.899601 .        .       
#> 62  .        .        2.663580 .        .       
#> 51  .        .        2.654786 .        .       
#> 50  .        .        2.590977 .        .       
#> 52  .        .        2.405257 .        .       
#> 49  .        .        2.361923 .        .       
#> 60  .        .        2.345778 .        .       
#> 47  .        .        2.327747 .        .       
#> 43  .        .        2.304942 .        .       
#> 45  .        .        2.091304 .        .       
#> 58  .        .        2.026959 .        .       
#> 59  .        .        1.935521 .        .       
#> 54  .        .        1.665083 .        .       
#> 57  .        .        1.574514 .        .       
#> 44  .        .        1.429971 .        .       
#> 46  .        .        1.383866 .        .       
#> 55  .        .        1.127204 .        .       
#> 48  .        .        1.078437 .        .       
#> 53  .        .        1.025282 .        .       
#> 78  .        .        .        2.929489 .       
#> 65  .        .        .        2.918540 .       
#> 73  .        .        .        2.836101 .       
#> 75  .        .        .        2.791648 .       
#> 67  .        .        .        2.722676 .       
#> 66  .        .        .        2.679633 .       
#> 71  .        .        .        2.155490 .       
#> 69  .        .        .        2.028676 .       
#> 79  .        .        .        2.011539 .       
#> 68  .        .        .        1.956569 .       
#> 77  .        .        .        1.773871 .       
#> 76  .        .        .        1.693923 .       
#> 63  .        .        .        1.634762 .       
#> 72  .        .        .        1.392946 .       
#> 74  .        .        .        1.310074 .       
#> 64  .        .        .        1.194024 .       
#> 70  .        .        .        1.107997 .       
#> 90  .        .        .        .        2.959062
#> 84  .        .        .        .        2.948355
#> 96  .        .        .        .        2.830710
#> 100 .        .        .        .        2.582274
#> 99  .        .        .        .        2.543355
#> 87  .        .        .        .        2.467835
#> 97  .        .        .        .        2.409062
#> 89  .        .        .        .        2.227856
#> 81  .        .        .        .        2.225751
#> 93  .        .        .        .        1.940571
#> 86  .        .        .        .        1.906229
#> 95  .        .        .        .        1.831589
#> 91  .        .        .        .        1.704240
#> 85  .        .        .        .        1.627769
#> 82  .        .        .        .        1.627278
#> 98  .        .        .        .        1.569177
#> 92  .        .        .        .        1.340232
#> 83  .        .        .        .        1.335422
#> 94  .        .        .        .        1.292074
#> 80  .        .        .        .        1.162234
#> 88  .        .        .        .        1.153976
#> 
#> $zC_obs
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>           C1       C2       C3       C4       C5
#> 20  2.930756 .        .        .        .       
#> 1   2.870189 .        .        .        .       
#> 8   2.865905 .        .        .        .       
#> 17  2.835739 .        .        .        .       
#> 12  2.729818 .        .        .        .       
#> 15  2.729529 .        .        .        .       
#> 10  2.567334 .        .        .        .       
#> 16  2.506458 .        .        .        .       
#> 3   2.325768 .        .        .        .       
#> 6   2.242860 .        .        .        .       
#> 11  2.039268 .        .        .        .       
#> 5   1.848004 .        .        .        .       
#> 4   1.832678 .        .        .        .       
#> 14  1.653258 .        .        .        .       
#> 2   1.634236 .        .        .        .       
#> 9   1.601352 .        .        .        .       
#> 19  1.428629 .        .        .        .       
#> 7   1.291971 .        .        .        .       
#> 18  1.277308 .        .        .        .       
#> 13  1.190104 .        .        .        .       
#> 34  .        2.883388 .        .        .       
#> 30  .        2.777024 .        .        .       
#> 25  .        2.724281 .        .        .       
#> 22  .        2.606328 .        .        .       
#> 23  .        2.559632 .        .        .       
#> 31  .        2.504702 .        .        .       
#> 35  .        2.188869 .        .        .       
#> 27  .        2.035704 .        .        .       
#> 33  .        1.997709 .        .        .       
#> 26  .        1.975963 .        .        .       
#> 29  .        1.764727 .        .        .       
#> 36  .        1.706320 .        .        .       
#> 21  .        1.665254 .        .        .       
#> 32  .        1.620141 .        .        .       
#> 28  .        1.544216 .        .        .       
#> 37  .        1.336067 .        .        .       
#> 38  .        1.302076 .        .        .       
#> 24  .        1.297295 .        .        .       
#> 39  .        1.044201 .        .        .       
#> 51  .        .        2.654786 .        .       
#> 50  .        .        2.590977 .        .       
#> 52  .        .        2.405257 .        .       
#> 49  .        .        2.361923 .        .       
#> 40  .        .        2.360504 .        .       
#> 47  .        .        2.327747 .        .       
#> 43  .        .        2.304942 .        .       
#> 45  .        .        2.091304 .        .       
#> 54  .        .        1.665083 .        .       
#> 44  .        .        1.429971 .        .       
#> 46  .        .        1.383866 .        .       
#> 41  .        .        1.218249 .        .       
#> 42  .        .        1.131645 .        .       
#> 55  .        .        1.127204 .        .       
#> 48  .        .        1.078437 .        .       
#> 53  .        .        1.025282 .        .       
#> 56  .        .        .        2.950460 .       
#> 65  .        .        .        2.918540 .       
#> 61  .        .        .        2.899601 .       
#> 73  .        .        .        2.836101 .       
#> 75  .        .        .        2.791648 .       
#> 67  .        .        .        2.722676 .       
#> 66  .        .        .        2.679633 .       
#> 62  .        .        .        2.663580 .       
#> 60  .        .        .        2.345778 .       
#> 71  .        .        .        2.155490 .       
#> 69  .        .        .        2.028676 .       
#> 58  .        .        .        2.026959 .       
#> 68  .        .        .        1.956569 .       
#> 59  .        .        .        1.935521 .       
#> 76  .        .        .        1.693923 .       
#> 63  .        .        .        1.634762 .       
#> 57  .        .        .        1.574514 .       
#> 72  .        .        .        1.392946 .       
#> 74  .        .        .        1.310074 .       
#> 64  .        .        .        1.194024 .       
#> 70  .        .        .        1.107997 .       
#> 90  .        .        .        .        2.959062
#> 84  .        .        .        .        2.948355
#> 78  .        .        .        .        2.929489
#> 96  .        .        .        .        2.830710
#> 100 .        .        .        .        2.582274
#> 99  .        .        .        .        2.543355
#> 87  .        .        .        .        2.467835
#> 97  .        .        .        .        2.409062
#> 89  .        .        .        .        2.227856
#> 81  .        .        .        .        2.225751
#> 79  .        .        .        .        2.011539
#> 93  .        .        .        .        1.940571
#> 86  .        .        .        .        1.906229
#> 95  .        .        .        .        1.831589
#> 77  .        .        .        .        1.773871
#> 91  .        .        .        .        1.704240
#> 85  .        .        .        .        1.627769
#> 82  .        .        .        .        1.627278
#> 98  .        .        .        .        1.569177
#> 92  .        .        .        .        1.340232
#> 83  .        .        .        .        1.335422
#> 94  .        .        .        .        1.292074
#> 80  .        .        .        .        1.162234
#> 88  .        .        .        .        1.153976
#> 
#> $zX
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>                                                 
#> 1   2.870189 .        .        .        .       
#> 8   2.865905 .        .        .        .       
#> 17  2.835739 .        .        .        .       
#> 12  2.729818 .        .        .        .       
#> 15  2.729529 .        .        .        .       
#> 10  2.567334 .        .        .        .       
#> 16  2.506458 .        .        .        .       
#> 3   2.325768 .        .        .        .       
#> 6   2.242860 .        .        .        .       
#> 11  2.039268 .        .        .        .       
#> 5   1.848004 .        .        .        .       
#> 4   1.832678 .        .        .        .       
#> 14  1.653258 .        .        .        .       
#> 2   1.634236 .        .        .        .       
#> 9   1.601352 .        .        .        .       
#> 7   1.291971 .        .        .        .       
#> 13  1.190104 .        .        .        .       
#> 20  .        2.930756 .        .        .       
#> 34  .        2.883388 .        .        .       
#> 30  .        2.777024 .        .        .       
#> 25  .        2.724281 .        .        .       
#> 22  .        2.606328 .        .        .       
#> 23  .        2.559632 .        .        .       
#> 31  .        2.504702 .        .        .       
#> 40  .        2.360504 .        .        .       
#> 35  .        2.188869 .        .        .       
#> 27  .        2.035704 .        .        .       
#> 33  .        1.997709 .        .        .       
#> 26  .        1.975963 .        .        .       
#> 29  .        1.764727 .        .        .       
#> 36  .        1.706320 .        .        .       
#> 21  .        1.665254 .        .        .       
#> 32  .        1.620141 .        .        .       
#> 28  .        1.544216 .        .        .       
#> 19  .        1.428629 .        .        .       
#> 37  .        1.336067 .        .        .       
#> 38  .        1.302076 .        .        .       
#> 24  .        1.297295 .        .        .       
#> 18  .        1.277308 .        .        .       
#> 41  .        1.218249 .        .        .       
#> 42  .        1.131645 .        .        .       
#> 39  .        1.044201 .        .        .       
#> 56  .        .        2.950460 .        .       
#> 61  .        .        2.899601 .        .       
#> 62  .        .        2.663580 .        .       
#> 51  .        .        2.654786 .        .       
#> 50  .        .        2.590977 .        .       
#> 52  .        .        2.405257 .        .       
#> 49  .        .        2.361923 .        .       
#> 60  .        .        2.345778 .        .       
#> 47  .        .        2.327747 .        .       
#> 43  .        .        2.304942 .        .       
#> 45  .        .        2.091304 .        .       
#> 58  .        .        2.026959 .        .       
#> 59  .        .        1.935521 .        .       
#> 54  .        .        1.665083 .        .       
#> 57  .        .        1.574514 .        .       
#> 44  .        .        1.429971 .        .       
#> 46  .        .        1.383866 .        .       
#> 55  .        .        1.127204 .        .       
#> 48  .        .        1.078437 .        .       
#> 53  .        .        1.025282 .        .       
#> 78  .        .        .        2.929489 .       
#> 65  .        .        .        2.918540 .       
#> 73  .        .        .        2.836101 .       
#> 75  .        .        .        2.791648 .       
#> 67  .        .        .        2.722676 .       
#> 66  .        .        .        2.679633 .       
#> 71  .        .        .        2.155490 .       
#> 69  .        .        .        2.028676 .       
#> 79  .        .        .        2.011539 .       
#> 68  .        .        .        1.956569 .       
#> 77  .        .        .        1.773871 .       
#> 76  .        .        .        1.693923 .       
#> 63  .        .        .        1.634762 .       
#> 72  .        .        .        1.392946 .       
#> 74  .        .        .        1.310074 .       
#> 64  .        .        .        1.194024 .       
#> 70  .        .        .        1.107997 .       
#> 90  .        .        .        .        2.959062
#> 84  .        .        .        .        2.948355
#> 96  .        .        .        .        2.830710
#> 100 .        .        .        .        2.582274
#> 99  .        .        .        .        2.543355
#> 87  .        .        .        .        2.467835
#> 97  .        .        .        .        2.409062
#> 89  .        .        .        .        2.227856
#> 81  .        .        .        .        2.225751
#> 93  .        .        .        .        1.940571
#> 86  .        .        .        .        1.906229
#> 95  .        .        .        .        1.831589
#> 91  .        .        .        .        1.704240
#> 85  .        .        .        .        1.627769
#> 82  .        .        .        .        1.627278
#> 98  .        .        .        .        1.569177
#> 92  .        .        .        .        1.340232
#> 83  .        .        .        .        1.335422
#> 94  .        .        .        .        1.292074
#> 80  .        .        .        .        1.162234
#> 88  .        .        .        .        1.153976
#> 
#> $ztheta_0
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    0    0    0    0    0
#> 
#> $ztheta_t
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    0    0    0    0    0
#> 
#> $ztheta_c
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    1    0    0    0    0
#> [2,]    0    1    0    0    0
#> [3,]    0    0    1    0    0
#> [4,]    0    0    0    1    0
#> [5,]    0    0    0    0    1
#> 
#> $ztheta_tc
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]    0    0    0    0    0
#> [2,]    0    0    0    0    0
#> [3,]    0    0    0    0    0
#> [4,]    0    0    0    0    0
#> [5,]    0    0    0    0    0
#> 
#> attr(,"class")
#> [1] "informative" "mediator"   
#> 
#> $model_name
#> [1] "informative_normal"
#> 
#> attr(,"class")
#> [1] "normal"  "outcome"

coef(o)
#>        C1        C2        C3        C4        C5       US1       US2       US3 
#> 1.6422149 1.7788470 1.2257354 1.7366038 1.1769008 0.8888388 0.7109887 1.0899153 
#>       US4       US5 
#> 0.7026465 1.5884116 

graph <- sample_tidygraph(o)
graph
#> # A tbl_graph: 100 nodes and 6998 edges
#> #
#> # An undirected multigraph with 1 component
#> #
#> # Node Data: 100 × 7 (active)
#>    name     C1    C2    C3    C4    C5     y
#>    <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 1      2.93     0     0     0     0  6.89
#>  2 2      2.87     0     0     0     0  8.62
#>  3 3      2.87     0     0     0     0  8.31
#>  4 4      2.84     0     0     0     0  7.68
#>  5 5      2.73     0     0     0     0  7.68
#>  6 6      2.73     0     0     0     0  7.34
#>  7 7      2.57     0     0     0     0  5.40
#>  8 8      2.51     0     0     0     0  5.51
#>  9 9      2.33     0     0     0     0  8.48
#> 10 10     2.24     0     0     0     0  7.52
#> # ℹ 90 more rows
#> #
#> # Edge Data: 6,998 × 2
#>    from    to
#>   <int> <int>
#> 1     3     7
#> 2    10    10
#> 3     4    12
#> # ℹ 6,995 more rows