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Mediator-pass through with normal errors

Usage

model_outcome_normal(mediator, beta_w = NULL, beta_x = NULL, sigma = 1)

Arguments

mediator

TODO

beta_w

TODO

beta_x

TODO

sigma

TODO

Value

TODO

Examples


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

o
#> $y
#>   [1] -3.80333495 -3.03091287 -3.04495951 -4.24957172 -2.04853177 -3.35809816
#>   [7] -2.48042668 -1.36520971 -1.61800905 -2.73970258 -3.33758369 -3.43808021
#>  [13] -2.29923751 -2.90481267 -1.54799494 -1.41901400 -0.75132410 -1.17102765
#>  [19] -1.59747404 -1.95383180 -0.55577688 -1.50143175  0.43530108  0.82993617
#>  [25] -1.38887095  1.05348759  0.20075418 -1.40329037  0.17717348 -1.34877644
#>  [31]  0.76234786  0.68485679  1.75064002  0.10336351  0.91736603  1.04548996
#>  [37]  0.55960950 -0.25568138  0.66271417  0.63611774  0.33262023  0.45205869
#>  [43] -0.83028958  1.07835929  0.12957374 -0.11477770  0.68321899 -0.27718608
#>  [49] -1.79339735 -1.64527698 -2.56379556  1.86084254 -1.81054247 -0.45805813
#>  [55] -2.49126765 -1.15649620  2.07972603 -1.09468514 -1.08556021 -0.45963380
#>  [61] -2.16477811 -0.84350571 -1.33971623 -0.09864137  3.05206644  2.88174472
#>  [67]  3.52064377  0.18711982  0.11141616 -0.78198648 -1.58667404 -0.41555966
#>  [73] -0.80686255  0.15742524 -0.83216979 -0.57957689 -0.30192680 -0.90919870
#>  [79]  1.23317536  0.95332635 -0.02134625  2.39208839  0.97604931  3.08821432
#>  [85]  4.96995863  5.55821097  5.20234450  4.71670031  3.56299424  3.66251291
#>  [91]  5.82961729  3.30417304  3.90468995  3.05266947  4.04766098  2.61324789
#>  [97]  2.91139546  2.52546382  2.87606307  2.45042280
#> 
#> $beta_w
#>        C1        C2        C3        C4        C5 
#> 0.7452323 0.7537690 0.7148711 1.2711129 0.7753766 
#> 
#> $beta_x
#>       US1       US2       US3       US4       US5 
#> 1.5446659 0.4522614 0.2113007 0.9657008 0.7248244 
#> 
#> $mediator
#> $n
#> [1] 100
#> 
#> $k
#> [1] 5
#> 
#> $X
#>                US1        US2          US3         US4         US5
#>   [1,] -3.76403831  0.2930287 -0.025060995 -0.08434292  0.06978469
#>   [2,] -3.59904942  0.2801844 -0.023962497 -0.08064592  0.06672582
#>   [3,] -3.58451412  0.2790528 -0.023865721 -0.08032022  0.06645634
#>   [4,] -3.54447792  0.2759360 -0.023599160 -0.07942310  0.06571408
#>   [5,] -3.46507199  0.2697543 -0.023070475 -0.07764381  0.06424190
#>   [6,] -3.36738614  0.2621495 -0.022420081 -0.07545491  0.06243082
#>   [7,] -3.29720882  0.2566862 -0.021952840 -0.07388241  0.06112975
#>   [8,] -3.12367458  0.2431767 -0.020797448 -0.06999393  0.05791245
#>   [9,] -3.04077492  0.2367230 -0.020245502 -0.06813635  0.05637550
#>  [10,] -2.76624405  0.2153508 -0.018417673 -0.06198478  0.05128574
#>  [11,] -2.69555899  0.2098480 -0.017947051 -0.06040090  0.04997525
#>  [12,] -2.49555606  0.1942779 -0.016615430 -0.05591932  0.04626723
#>  [13,] -2.47521895  0.1926947 -0.016480026 -0.05546362  0.04589018
#>  [14,] -2.19403421  0.1708046 -0.014607896 -0.04916295  0.04067706
#>  [15,] -2.16732808  0.1687255 -0.014430086 -0.04856453  0.04018193
#>  [16,] -2.14896672  0.1672961 -0.014307836 -0.04815310  0.03984151
#>  [17,] -2.14308638  0.1668383 -0.014268685 -0.04802134  0.03973249
#>  [18,] -2.07194121  0.1612997 -0.013795000 -0.04642715  0.03841347
#>  [19,] -1.94697962  0.1515715 -0.012963005 -0.04362706  0.03609670
#>  [20,] -1.89938232  0.1478661 -0.012646101 -0.04256052  0.03521426
#>  [21,] -1.55879666  0.1213516 -0.010378480 -0.03492883  0.02889985
#>  [22,] -1.54112224  0.1199757 -0.010260803 -0.03453279  0.02857217
#>  [23,] -1.35146965  0.1052113 -0.008998095 -0.03028314  0.02505604
#>  [24,] -0.20684377 -2.1308687  2.619744072 -0.68866619  0.24096139
#>  [25,] -0.19604249 -2.0195958  2.482942322 -0.65270438  0.22837851
#>  [26,] -0.17321865 -1.7844686  2.193870907 -0.57671462  0.20179001
#>  [27,] -0.17255227 -1.7776037  2.185431009 -0.57449598  0.20101372
#>  [28,] -0.16944473 -1.7455903  2.146072988 -0.56414973  0.19739361
#>  [29,] -0.15538915 -1.6007922  1.968054481 -0.51735305  0.18101965
#>  [30,] -0.15471648 -1.5938625  1.959534928 -0.51511347  0.18023603
#>  [31,] -0.15388014 -1.5852466  1.948942363 -0.51232894  0.17926173
#>  [32,] -0.15270923 -1.5731841  1.934112480 -0.50843053  0.17789770
#>  [33,] -0.15207250 -1.5666246  1.926048046 -0.50631059  0.17715594
#>  [34,] -0.14854921 -1.5303283  1.881424390 -0.49458013  0.17305150
#>  [35,] -0.13712440 -1.4126319  1.736725426 -0.45654234  0.15974224
#>  [36,] -0.13513886 -1.3921772  1.711577987 -0.44993170  0.15742920
#>  [37,] -0.12800544 -1.3186899  1.621230849 -0.42618166  0.14911916
#>  [38,] -0.11607170 -1.1957506  1.470086103 -0.38644943  0.13521702
#>  [39,] -0.11551789 -1.1900454  1.463071970 -0.38460558  0.13457187
#>  [40,] -0.11401169 -1.1745287  1.443995395 -0.37959082  0.13281723
#>  [41,] -0.10462312 -1.0778093  1.325086065 -0.34833249  0.12188007
#>  [42,] -0.09520580 -0.9807937  1.205812703 -0.31697846  0.11090942
#>  [43,] -0.09356566 -0.9638972  1.185039672 -0.31151774  0.10899874
#>  [44,] -0.09165711 -0.9442357  1.160867321 -0.30516343  0.10677539
#>  [45,] -0.09069334 -0.9343071  1.148660855 -0.30195465  0.10565266
#>  [46,] -0.08945937 -0.9215950  1.133032205 -0.29784626  0.10421515
#>  [47,] -0.08534590 -0.8792187  1.080933803 -0.28415087  0.09942319
#>  [48,] -0.08206614 -0.8454312  1.039394607 -0.27323124  0.09560246
#>  [49,] -0.21482353 -2.6161337 -2.268696757 -0.61103045  0.23356851
#>  [50,] -0.21434994 -2.6103663 -2.263695311 -0.60968340  0.23305359
#>  [51,] -0.20566621 -2.5046153 -2.171988638 -0.58498395  0.22361214
#>  [52,] -0.20472506 -2.4931540 -2.162049400 -0.58230701  0.22258887
#>  [53,] -0.18323454 -2.2314412 -1.935093503 -0.52118074  0.19922314
#>  [54,] -0.18288741 -2.2272137 -1.931427480 -0.52019337  0.19884572
#>  [55,] -0.17861918 -2.1752350 -1.886351785 -0.50805308  0.19420505
#>  [56,] -0.16926198 -2.0612824 -1.787532772 -0.48143805  0.18403136
#>  [57,] -0.16873067 -2.0548122 -1.781921826 -0.47992685  0.18345370
#>  [58,] -0.15533493 -1.8916780 -1.640452749 -0.44182484  0.16888908
#>  [59,] -0.14941206 -1.8195489 -1.577902836 -0.42497821  0.16244939
#>  [60,] -0.14434508 -1.7578430 -1.524391804 -0.41056602  0.15694029
#>  [61,] -0.14253972 -1.7358571 -1.505325756 -0.40543095  0.15497738
#>  [62,] -0.12356622 -1.5047968 -1.304951517 -0.35146394  0.13434831
#>  [63,] -0.12073734 -1.4703465 -1.275076436 -0.34341766  0.13127259
#>  [64,] -0.11640177 -1.4175476 -1.229289523 -0.33108582  0.12655870
#>  [65,] -0.10881206 -1.3251197 -1.149136543 -0.30949814  0.11830673
#>  [66,] -0.09588611 -1.1677068 -1.012628884 -0.27273239  0.10425290
#>  [67,] -0.07901605 -0.9622622 -0.834468498 -0.22474827  0.08591080
#>  [68,] -0.16402427 -0.5170510  0.062242616  0.36153222 -3.68470240
#>  [69,] -0.16289541 -0.5134925  0.061814245  0.35904406 -3.65934323
#>  [70,] -0.15733522 -0.4959653  0.059704310  0.34678864 -3.53443715
#>  [71,] -0.14863055 -0.4685257  0.056401131  0.32760233 -3.33889215
#>  [72,] -0.12786162 -0.4030561  0.048519903  0.28182473 -2.87233108
#>  [73,] -0.11959171 -0.3769870  0.045381703  0.26359670 -2.68655274
#>  [74,] -0.11858053 -0.3737995  0.044997991  0.26136793 -2.66383732
#>  [75,] -0.11523489 -0.3632531  0.043728412  0.25399366 -2.58867947
#>  [76,] -0.11371331 -0.3584566  0.043151015  0.25063989 -2.55449813
#>  [77,] -0.10885909 -0.3431547  0.041308974  0.23994051 -2.44545113
#>  [78,] -0.09824729 -0.3097033  0.037282096  0.21655065 -2.20706385
#>  [79,] -0.08706093 -0.2744408  0.033037185  0.19189436 -1.95576925
#>  [80,] -0.08157273 -0.2571404  0.030954567  0.17979760 -1.83248026
#>  [81,] -0.08019508 -0.2527977  0.030431788  0.17676108 -1.80153225
#>  [82,] -0.06027731 -0.1900112  0.022873550  0.13285954 -1.35409193
#>  [83,] -0.05976367 -0.1883920  0.022678638  0.13172740 -1.34255330
#>  [84,] -0.05674070 -0.1788628  0.021531505  0.12506436 -1.27464418
#>  [85,] -0.19561565 -0.9745131  0.152518240  3.57710790  0.45148500
#>  [86,] -0.19263577 -0.9596680  0.150194877  3.52261660  0.44460737
#>  [87,] -0.17606123 -0.8770973  0.137271983  3.21952768  0.40635298
#>  [88,] -0.16991854 -0.8464959  0.132482636  3.10720006  0.39217554
#>  [89,] -0.16768581 -0.8353729  0.130741811  3.06637138  0.38702234
#>  [90,] -0.15541550 -0.7742450  0.121174859  2.84199152  0.35870222
#>  [91,] -0.15510051 -0.7726758  0.120929265  2.83623145  0.35797521
#>  [92,] -0.14922988 -0.7434296  0.116352035  2.72887875  0.34442568
#>  [93,] -0.14081948 -0.7015309  0.109794582  2.57508260  0.32501429
#>  [94,] -0.13809454 -0.6879559  0.107669999  2.52525341  0.31872509
#>  [95,] -0.13797639 -0.6873673  0.107577877  2.52309281  0.31845239
#>  [96,] -0.12801937 -0.6377637  0.099814558  2.34101472  0.29547139
#>  [97,] -0.12068501 -0.6012255  0.094096076  2.20689550  0.27854352
#>  [98,] -0.10129023 -0.5046051  0.078974295  1.85223469  0.23377997
#>  [99,] -0.07363229 -0.3668195  0.057409863  1.34647026  0.16994487
#> [100,] -0.07083771 -0.3528975  0.055230975  1.29536741  0.16349492
#> 
#> $W
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>           C1       C2       C3       C4       C5
#> 10  2.986057 .        .        .        .       
#> 14  2.855170 .        .        .        .       
#> 7   2.843639 .        .        .        .       
#> 8   2.811877 .        .        .        .       
#> 5   2.671388 .        .        .        .       
#> 11  2.615716 .        .        .        .       
#> 1   2.478049 .        .        .        .       
#> 6   2.412284 .        .        .        .       
#> 13  2.138420 .        .        .        .       
#> 15  1.963621 .        .        .        .       
#> 12  1.740554 .        .        .        .       
#> 2   1.719368 .        .        .        .       
#> 3   1.704801 .        .        .        .       
#> 9   1.700136 .        .        .        .       
#> 16  1.506803 .        .        .        .       
#> 4   1.072137 .        .        .        .       
#> 23  .        2.748884 .        .        .       
#> 35  .        2.736189 .        .        .       
#> 34  .        2.593307 .        .        .       
#> 28  .        2.241464 .        .        .       
#> 17  .        2.194495 .        .        .       
#> 43  .        2.055532 .        .        .       
#> 42  .        2.046634 .        .        .       
#> 25  .        2.035571 .        .        .       
#> 33  .        2.020082 .        .        .       
#> 38  .        2.011659 .        .        .       
#> 18  .        1.979755 .        .        .       
#> 39  .        1.965052 .        .        .       
#> 40  .        1.813921 .        .        .       
#> 41  .        1.693293 .        .        .       
#> 22  .        1.643696 .        .        .       
#> 19  .        1.544563 .        .        .       
#> 29  .        1.535430 .        .        .       
#> 24  .        1.528104 .        .        .       
#> 27  .        1.508180 .        .        .       
#> 37  .        1.383985 .        .        .       
#> 36  .        1.259410 .        .        .       
#> 32  .        1.237713 .        .        .       
#> 20  .        1.236612 .        .        .       
#> 21  .        1.222591 .        .        .       
#> 31  .        1.212467 .        .        .       
#> 26  .        1.128980 .        .        .       
#> 30  .        1.085595 .        .        .       
#> 63  .        .        2.791192 .        .       
#> 64  .        .        2.785038 .        .       
#> 57  .        .        2.659983 .        .       
#> 59  .        .        2.380758 .        .       
#> 62  .        .        2.376247 .        .       
#> 53  .        .        2.320790 .        .       
#> 48  .        .        2.291386 .        .       
#> 46  .        .        2.282571 .        .       
#> 49  .        .        2.199213 .        .       
#> 52  .        .        2.192310 .        .       
#> 55  .        .        2.018259 .        .       
#> 56  .        .        1.941304 .        .       
#> 50  .        .        1.875469 .        .       
#> 61  .        .        1.852012 .        .       
#> 44  .        .        1.787656 .        .       
#> 54  .        .        1.605490 .        .       
#> 58  .        .        1.512403 .        .       
#> 51  .        .        1.413790 .        .       
#> 60  .        .        1.245844 .        .       
#> 45  .        .        1.199718 .        .       
#> 47  .        .        1.183394 .        .       
#> 74  .        .        .        2.938296 .       
#> 67  .        .        .        2.672211 .       
#> 75  .        .        .        2.157187 .       
#> 71  .        .        .        2.078599 .       
#> 68  .        .        .        2.051153 .       
#> 73  .        .        .        1.963593 .       
#> 70  .        .        .        1.772178 .       
#> 72  .        .        .        1.570399 .       
#> 65  .        .        .        1.568734 .       
#> 69  .        .        .        1.446553 .       
#> 77  .        .        .        1.087278 .       
#> 76  .        .        .        1.078013 .       
#> 66  .        .        .        1.026652 .       
#> 90  .        .        .        .        2.959175
#> 78  .        .        .        .        2.958659
#> 88  .        .        .        .        2.914096
#> 81  .        .        .        .        2.838002
#> 83  .        .        .        .        2.680988
#> 89  .        .        .        .        2.663365
#> 97  .        .        .        .        2.570442
#> 98  .        .        .        .        2.536666
#> 87  .        .        .        .        2.351047
#> 85  .        .        .        .        2.346282
#> 82  .        .        .        .        2.306359
#> 92  .        .        .        .        2.257474
#> 80  .        .        .        .        2.138948
#> 91  .        .        .        .        2.130246
#> 95  .        .        .        .        2.089024
#> 86  .        .        .        .        2.087237
#> 93  .        .        .        .        1.936612
#> 100 .        .        .        .        1.825662
#> 94  .        .        .        .        1.532267
#> 79  .        .        .        .        1.471403
#> 99  .        .        .        .        1.113872
#> 96  .        .        .        .        1.071597
#> 84  .        .        .        .        1.023485
#> 
#> $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: 6706
#> Expected degree: 67.1
#> Expected density: 1.35467
#> $Theta
#>            US1        US2          US3         US4         US5
#> C1 -1.32979852  0.1035242 -0.008853808 -0.02979754  0.02465426
#> C2 -0.38631533 -0.5046354  0.650226308 -0.17901651  0.06621933
#> C3 -0.06964710 -0.8239469 -0.435708441 -0.20436135  0.07672716
#> C4 -0.06282931 -0.3433414 -0.152259974  0.05722047 -1.03231636
#> C5 -0.05219517 -0.2366172  0.035575214  0.74869842 -0.19648162
#> 
#> $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: 6706
#> Expected degree: 67.1
#> Expected density: 1.35467
#> $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: 6947
#> Expected degree: 69.5
#> Expected density: 1.40345
#> $zC_true
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>           C1       C2       C3       C4       C5
#> 10  2.986057 .        .        .        .       
#> 14  2.855170 .        .        .        .       
#> 7   2.843639 .        .        .        .       
#> 8   2.811877 .        .        .        .       
#> 23  2.748884 .        .        .        .       
#> 5   2.671388 .        .        .        .       
#> 11  2.615716 .        .        .        .       
#> 1   2.478049 .        .        .        .       
#> 6   2.412284 .        .        .        .       
#> 17  2.194495 .        .        .        .       
#> 13  2.138420 .        .        .        .       
#> 18  1.979755 .        .        .        .       
#> 15  1.963621 .        .        .        .       
#> 12  1.740554 .        .        .        .       
#> 2   1.719368 .        .        .        .       
#> 3   1.704801 .        .        .        .       
#> 9   1.700136 .        .        .        .       
#> 22  1.643696 .        .        .        .       
#> 19  1.544563 .        .        .        .       
#> 16  1.506803 .        .        .        .       
#> 20  1.236612 .        .        .        .       
#> 21  1.222591 .        .        .        .       
#> 4   1.072137 .        .        .        .       
#> 35  .        2.736189 .        .        .       
#> 34  .        2.593307 .        .        .       
#> 48  .        2.291386 .        .        .       
#> 46  .        2.282571 .        .        .       
#> 28  .        2.241464 .        .        .       
#> 43  .        2.055532 .        .        .       
#> 42  .        2.046634 .        .        .       
#> 25  .        2.035571 .        .        .       
#> 33  .        2.020082 .        .        .       
#> 38  .        2.011659 .        .        .       
#> 39  .        1.965052 .        .        .       
#> 40  .        1.813921 .        .        .       
#> 44  .        1.787656 .        .        .       
#> 41  .        1.693293 .        .        .       
#> 29  .        1.535430 .        .        .       
#> 24  .        1.528104 .        .        .       
#> 27  .        1.508180 .        .        .       
#> 37  .        1.383985 .        .        .       
#> 36  .        1.259410 .        .        .       
#> 32  .        1.237713 .        .        .       
#> 31  .        1.212467 .        .        .       
#> 45  .        1.199718 .        .        .       
#> 47  .        1.183394 .        .        .       
#> 26  .        1.128980 .        .        .       
#> 30  .        1.085595 .        .        .       
#> 63  .        .        2.791192 .        .       
#> 64  .        .        2.785038 .        .       
#> 67  .        .        2.672211 .        .       
#> 57  .        .        2.659983 .        .       
#> 59  .        .        2.380758 .        .       
#> 62  .        .        2.376247 .        .       
#> 53  .        .        2.320790 .        .       
#> 49  .        .        2.199213 .        .       
#> 52  .        .        2.192310 .        .       
#> 55  .        .        2.018259 .        .       
#> 56  .        .        1.941304 .        .       
#> 50  .        .        1.875469 .        .       
#> 61  .        .        1.852012 .        .       
#> 54  .        .        1.605490 .        .       
#> 65  .        .        1.568734 .        .       
#> 58  .        .        1.512403 .        .       
#> 51  .        .        1.413790 .        .       
#> 60  .        .        1.245844 .        .       
#> 66  .        .        1.026652 .        .       
#> 78  .        .        .        2.958659 .       
#> 74  .        .        .        2.938296 .       
#> 81  .        .        .        2.838002 .       
#> 83  .        .        .        2.680988 .       
#> 82  .        .        .        2.306359 .       
#> 75  .        .        .        2.157187 .       
#> 80  .        .        .        2.138948 .       
#> 71  .        .        .        2.078599 .       
#> 68  .        .        .        2.051153 .       
#> 73  .        .        .        1.963593 .       
#> 70  .        .        .        1.772178 .       
#> 72  .        .        .        1.570399 .       
#> 79  .        .        .        1.471403 .       
#> 69  .        .        .        1.446553 .       
#> 77  .        .        .        1.087278 .       
#> 76  .        .        .        1.078013 .       
#> 84  .        .        .        1.023485 .       
#> 90  .        .        .        .        2.959175
#> 88  .        .        .        .        2.914096
#> 89  .        .        .        .        2.663365
#> 97  .        .        .        .        2.570442
#> 98  .        .        .        .        2.536666
#> 87  .        .        .        .        2.351047
#> 85  .        .        .        .        2.346282
#> 92  .        .        .        .        2.257474
#> 91  .        .        .        .        2.130246
#> 95  .        .        .        .        2.089024
#> 86  .        .        .        .        2.087237
#> 93  .        .        .        .        1.936612
#> 100 .        .        .        .        1.825662
#> 94  .        .        .        .        1.532267
#> 99  .        .        .        .        1.113872
#> 96  .        .        .        .        1.071597
#> 
#> $zC_obs
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>           C1       C2       C3       C4       C5
#> 10  2.986057 .        .        .        .       
#> 14  2.855170 .        .        .        .       
#> 7   2.843639 .        .        .        .       
#> 8   2.811877 .        .        .        .       
#> 5   2.671388 .        .        .        .       
#> 11  2.615716 .        .        .        .       
#> 1   2.478049 .        .        .        .       
#> 6   2.412284 .        .        .        .       
#> 13  2.138420 .        .        .        .       
#> 15  1.963621 .        .        .        .       
#> 12  1.740554 .        .        .        .       
#> 2   1.719368 .        .        .        .       
#> 3   1.704801 .        .        .        .       
#> 9   1.700136 .        .        .        .       
#> 16  1.506803 .        .        .        .       
#> 4   1.072137 .        .        .        .       
#> 23  .        2.748884 .        .        .       
#> 35  .        2.736189 .        .        .       
#> 34  .        2.593307 .        .        .       
#> 28  .        2.241464 .        .        .       
#> 17  .        2.194495 .        .        .       
#> 43  .        2.055532 .        .        .       
#> 42  .        2.046634 .        .        .       
#> 25  .        2.035571 .        .        .       
#> 33  .        2.020082 .        .        .       
#> 38  .        2.011659 .        .        .       
#> 18  .        1.979755 .        .        .       
#> 39  .        1.965052 .        .        .       
#> 40  .        1.813921 .        .        .       
#> 41  .        1.693293 .        .        .       
#> 22  .        1.643696 .        .        .       
#> 19  .        1.544563 .        .        .       
#> 29  .        1.535430 .        .        .       
#> 24  .        1.528104 .        .        .       
#> 27  .        1.508180 .        .        .       
#> 37  .        1.383985 .        .        .       
#> 36  .        1.259410 .        .        .       
#> 32  .        1.237713 .        .        .       
#> 20  .        1.236612 .        .        .       
#> 21  .        1.222591 .        .        .       
#> 31  .        1.212467 .        .        .       
#> 26  .        1.128980 .        .        .       
#> 30  .        1.085595 .        .        .       
#> 63  .        .        2.791192 .        .       
#> 64  .        .        2.785038 .        .       
#> 57  .        .        2.659983 .        .       
#> 59  .        .        2.380758 .        .       
#> 62  .        .        2.376247 .        .       
#> 53  .        .        2.320790 .        .       
#> 48  .        .        2.291386 .        .       
#> 46  .        .        2.282571 .        .       
#> 49  .        .        2.199213 .        .       
#> 52  .        .        2.192310 .        .       
#> 55  .        .        2.018259 .        .       
#> 56  .        .        1.941304 .        .       
#> 50  .        .        1.875469 .        .       
#> 61  .        .        1.852012 .        .       
#> 44  .        .        1.787656 .        .       
#> 54  .        .        1.605490 .        .       
#> 58  .        .        1.512403 .        .       
#> 51  .        .        1.413790 .        .       
#> 60  .        .        1.245844 .        .       
#> 45  .        .        1.199718 .        .       
#> 47  .        .        1.183394 .        .       
#> 74  .        .        .        2.938296 .       
#> 67  .        .        .        2.672211 .       
#> 75  .        .        .        2.157187 .       
#> 71  .        .        .        2.078599 .       
#> 68  .        .        .        2.051153 .       
#> 73  .        .        .        1.963593 .       
#> 70  .        .        .        1.772178 .       
#> 72  .        .        .        1.570399 .       
#> 65  .        .        .        1.568734 .       
#> 69  .        .        .        1.446553 .       
#> 77  .        .        .        1.087278 .       
#> 76  .        .        .        1.078013 .       
#> 66  .        .        .        1.026652 .       
#> 90  .        .        .        .        2.959175
#> 78  .        .        .        .        2.958659
#> 88  .        .        .        .        2.914096
#> 81  .        .        .        .        2.838002
#> 83  .        .        .        .        2.680988
#> 89  .        .        .        .        2.663365
#> 97  .        .        .        .        2.570442
#> 98  .        .        .        .        2.536666
#> 87  .        .        .        .        2.351047
#> 85  .        .        .        .        2.346282
#> 82  .        .        .        .        2.306359
#> 92  .        .        .        .        2.257474
#> 80  .        .        .        .        2.138948
#> 91  .        .        .        .        2.130246
#> 95  .        .        .        .        2.089024
#> 86  .        .        .        .        2.087237
#> 93  .        .        .        .        1.936612
#> 100 .        .        .        .        1.825662
#> 94  .        .        .        .        1.532267
#> 79  .        .        .        .        1.471403
#> 99  .        .        .        .        1.113872
#> 96  .        .        .        .        1.071597
#> 84  .        .        .        .        1.023485
#> 
#> $zX
#> 100 x 5 sparse Matrix of class "dgCMatrix"
#>                                                 
#> 10  2.986057 .        .        .        .       
#> 14  2.855170 .        .        .        .       
#> 7   2.843639 .        .        .        .       
#> 8   2.811877 .        .        .        .       
#> 23  2.748884 .        .        .        .       
#> 5   2.671388 .        .        .        .       
#> 11  2.615716 .        .        .        .       
#> 1   2.478049 .        .        .        .       
#> 6   2.412284 .        .        .        .       
#> 17  2.194495 .        .        .        .       
#> 13  2.138420 .        .        .        .       
#> 18  1.979755 .        .        .        .       
#> 15  1.963621 .        .        .        .       
#> 12  1.740554 .        .        .        .       
#> 2   1.719368 .        .        .        .       
#> 3   1.704801 .        .        .        .       
#> 9   1.700136 .        .        .        .       
#> 22  1.643696 .        .        .        .       
#> 19  1.544563 .        .        .        .       
#> 16  1.506803 .        .        .        .       
#> 20  1.236612 .        .        .        .       
#> 21  1.222591 .        .        .        .       
#> 4   1.072137 .        .        .        .       
#> 35  .        2.736189 .        .        .       
#> 34  .        2.593307 .        .        .       
#> 48  .        2.291386 .        .        .       
#> 46  .        2.282571 .        .        .       
#> 28  .        2.241464 .        .        .       
#> 43  .        2.055532 .        .        .       
#> 42  .        2.046634 .        .        .       
#> 25  .        2.035571 .        .        .       
#> 33  .        2.020082 .        .        .       
#> 38  .        2.011659 .        .        .       
#> 39  .        1.965052 .        .        .       
#> 40  .        1.813921 .        .        .       
#> 44  .        1.787656 .        .        .       
#> 41  .        1.693293 .        .        .       
#> 29  .        1.535430 .        .        .       
#> 24  .        1.528104 .        .        .       
#> 27  .        1.508180 .        .        .       
#> 37  .        1.383985 .        .        .       
#> 36  .        1.259410 .        .        .       
#> 32  .        1.237713 .        .        .       
#> 31  .        1.212467 .        .        .       
#> 45  .        1.199718 .        .        .       
#> 47  .        1.183394 .        .        .       
#> 26  .        1.128980 .        .        .       
#> 30  .        1.085595 .        .        .       
#> 63  .        .        2.791192 .        .       
#> 64  .        .        2.785038 .        .       
#> 67  .        .        2.672211 .        .       
#> 57  .        .        2.659983 .        .       
#> 59  .        .        2.380758 .        .       
#> 62  .        .        2.376247 .        .       
#> 53  .        .        2.320790 .        .       
#> 49  .        .        2.199213 .        .       
#> 52  .        .        2.192310 .        .       
#> 55  .        .        2.018259 .        .       
#> 56  .        .        1.941304 .        .       
#> 50  .        .        1.875469 .        .       
#> 61  .        .        1.852012 .        .       
#> 54  .        .        1.605490 .        .       
#> 65  .        .        1.568734 .        .       
#> 58  .        .        1.512403 .        .       
#> 51  .        .        1.413790 .        .       
#> 60  .        .        1.245844 .        .       
#> 66  .        .        1.026652 .        .       
#> 78  .        .        .        2.958659 .       
#> 74  .        .        .        2.938296 .       
#> 81  .        .        .        2.838002 .       
#> 83  .        .        .        2.680988 .       
#> 82  .        .        .        2.306359 .       
#> 75  .        .        .        2.157187 .       
#> 80  .        .        .        2.138948 .       
#> 71  .        .        .        2.078599 .       
#> 68  .        .        .        2.051153 .       
#> 73  .        .        .        1.963593 .       
#> 70  .        .        .        1.772178 .       
#> 72  .        .        .        1.570399 .       
#> 79  .        .        .        1.471403 .       
#> 69  .        .        .        1.446553 .       
#> 77  .        .        .        1.087278 .       
#> 76  .        .        .        1.078013 .       
#> 84  .        .        .        1.023485 .       
#> 90  .        .        .        .        2.959175
#> 88  .        .        .        .        2.914096
#> 89  .        .        .        .        2.663365
#> 97  .        .        .        .        2.570442
#> 98  .        .        .        .        2.536666
#> 87  .        .        .        .        2.351047
#> 85  .        .        .        .        2.346282
#> 92  .        .        .        .        2.257474
#> 91  .        .        .        .        2.130246
#> 95  .        .        .        .        2.089024
#> 86  .        .        .        .        2.087237
#> 93  .        .        .        .        1.936612
#> 100 .        .        .        .        1.825662
#> 94  .        .        .        .        1.532267
#> 99  .        .        .        .        1.113872
#> 96  .        .        .        .        1.071597
#> 
#> $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 
#> 0.7452323 0.7537690 0.7148711 1.2711129 0.7753766 1.5446659 0.4522614 0.2113007 
#>       US4       US5 
#> 0.9657008 0.7248244 

graph <- sample_tidygraph(o)
graph
#> # A tbl_graph: 100 nodes and 6753 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      2.99     0     0     0     0 -3.80
#>  2 2      2.86     0     0     0     0 -3.03
#>  3 3      2.84     0     0     0     0 -3.04
#>  4 4      2.81     0     0     0     0 -4.25
#>  5 5      2.67     0     0     0     0 -2.05
#>  6 6      2.62     0     0     0     0 -3.36
#>  7 7      2.48     0     0     0     0 -2.48
#>  8 8      2.41     0     0     0     0 -1.37
#>  9 9      2.14     0     0     0     0 -1.62
#> 10 10     1.96     0     0     0     0 -2.74
#> # ℹ 90 more rows
#> #
#> # Edge Data: 6,753 × 2
#>    from    to
#>   <int> <int>
#> 1     2    16
#> 2     6    10
#> 3     3    19
#> # ℹ 6,750 more rows