simcausal
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Simulating Longitudinal and Network Data with Causal Inference Applications
https://cran.r-project.org/web/packages/simcausal/index.html
Hi, I'd like to use simcausal for mediation analysis but wonder how this can best be done. For natural direct and indirect effects I need to simulate the crossworld counterfactual...
add S3 method `plot` for DAG object.
Simulated data contains two ID columns
I've run into the issue a few times, where when I call `simobs` get a `cannot find function 'melt'` error. When I run `library(data.table)`, the issue goes away. I have...
THIS no longer works, because the dimensions of catprob.W0 and catprob.W1 (1 row) do not match the dims of W (n rows) ``` R D
`latent.v` does not appear to work when output data is in long format ``` sim(DAG, wide=FALSE) ```
I am trying to perform a deterministic intervention on a DAG. ``` r library(simcausal) library(rje) D
Allow non-existing time-point references to default to some value, for example, instead of doing this ``` R node("TI", t=0:7, distr="rbern", prob=plogis(-5 - 0.3*CVD + 0.5*A1C[t] + 1.5*{if (t==0) {0} else...
using as.integer() in node formulas prints it to the terminal: ``` R library(simcausal) D