Title
Examples
set.seed(26)
mu <- model_mediator_uninformative(n = 100, k = 5, dim_w = 3)
graph <- sample_tidygraph(mu)
graph
#> # A tbl_graph: 100 nodes and 505 edges
#> #
#> # An undirected multigraph with 2 components
#> #
#> # Node Data: 100 × 5 (active)
#> name intercept trt C1 C2
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.560 0.0687 2.69
#> 2 2 1 1.89 0.261 -0.531
#> 3 3 1 0.936 1.14 2.17
#> 4 4 1 0.498 1.05 1.09
#> 5 5 1 0.546 2.41 0.971
#> 6 6 1 0.410 1.61 1.11
#> 7 7 1 1.64 1.99 -0.485
#> 8 8 1 0.951 0.226 0.142
#> 9 9 1 1.66 0.370 0.853
#> 10 10 1 1.66 2.81 -1.41
#> # ℹ 90 more rows
#> #
#> # Edge Data: 505 × 2
#> from to
#> <int> <int>
#> 1 5 7
#> 2 1 11
#> 3 2 12
#> # ℹ 502 more rows
coef(mu)
#> US1 US2 US3 US4 US5
#> intercept 0.138644945 -0.184701513 0.237370287 -0.04376545 -0.080108810
#> trt 0.010460058 -0.007206836 -0.028634771 -0.02931474 -0.009289389
#> C1 0.005761567 0.023950632 -0.009514605 -0.00828747 -0.001619688
#> C2 0.051424597 0.009627862 -0.078646970 -0.02355857 0.008428417
fit <- nodelm(US(A, 5) ~ . - name - 1, graph = graph)
fit
#>
#> Call:
#> stats::lm(formula = formula, data = data)
#>
#> Coefficients:
#> 1 2 3 4 5
#> intercept 0.131644 -0.166899 0.213331 -0.038863 -0.068322
#> trt 0.013517 -0.013989 -0.011209 -0.012078 -0.003860
#> C1 0.004623 0.008259 0.001589 -0.016803 -0.012861
#> C2 0.047880 0.009855 -0.080084 -0.033211 0.004270
#>