| +.DAG | Adding Node(s) to DAG |
| A | Subsetting/Indexing Actions Defined for 'DAG' Object |
| action | Define and Add Actions (Interventions) |
| add.action | Define and Add Actions (Interventions) |
| add.nodes | Adding Node(s) to DAG |
| DAG.empty | Initialize an empty DAG object |
| Define_sVar | Class for defining and evaluating user-specified summary measures (exprs_list) |
| DF.to.long | Convert Data from Wide to Long Format Using 'reshape' |
| DF.to.longDT | Faster Conversion of Data from Wide to Long Format Using 'dcast.data.table' |
| distr.list | List All Custom Distribution Functions in 'simcausal'. |
| doLTCF | Missing Variable Imputation with Last Time Point Value Carried Forward (LTCF) |
| eval.target | Evaluate the True Value of the Causal Target Parameter |
| igraph.to.sparseAdjMat | Convert igraph Network Object into Sparse Adjacency Matrix |
| N | Subsetting/Indexing 'DAG' Nodes |
| net.list | List All Custom Network Generator Functions in 'simcausal'. |
| NetInd.to.sparseAdjMat | Convert Network IDs Matrix into Sparse Adjacency Matrix |
| NetIndClass | R6 class for creating and storing a friend matrix (network IDs) for network data |
| network | Define a Network Generator |
| node | Create Node Object(s) |
| parents | Show Node Parents Given DAG Object |
| plotDAG | Plot DAG |
| plotSurvEst | (EXPERIMENTAL) Plot Discrete Survival Function(s) |
| print.DAG | Print DAG Object |
| print.DAG.action | Print Action Object |
| print.DAG.node | Print DAG.node Object |
| rbern | Random Sample from Bernoulli Distribution |
| rcat.b0 | Random Sample from Base 1 (rcat.b1) or Base 0 (rcat.b0) Categorical (Integer) Distribution |
| rcat.b1 | Random Sample from Base 1 (rcat.b1) or Base 0 (rcat.b0) Categorical (Integer) Distribution |
| rcat.factor | Random Sample for a Categorical Factor |
| rcategor | Random Sample for a Categorical Factor |
| rcategor.int | Random Sample from Base 1 (rcat.b1) or Base 0 (rcat.b0) Categorical (Integer) Distribution |
| rconst | Constant (Degenerate) Distribution (Returns its Own Argument 'const') |
| rdistr.template | Template for Writing Custom Distribution Functions |
| rnet.gnm | Call 'igraph::sample_gnm' to Generate Random Graph Object According to the G(n,m) Erdos-Renyi Model |
| rnet.gnp | Call 'igraph::sample_gnp' to Generate Random Graph Object According to the G(n,p) Erdos-Renyi Model |
| rnet.SmWorld | Call 'igraph::sample_smallworld' to Generate Random Graph Object from the Watts-Strogatz Small-World Model |
| set.DAG | Create and Lock DAG Object |
| set.targetE | Define Non-Parametric Causal Parameters |
| set.targetMSM | Define Causal Parameters with a Working Marginal Structural Model (MSM) |
| sim | Simulate Observed or Full Data from 'DAG' Object |
| simcausal | Simulating Longitudinal Data with Causal Inference Applications |
| simfull | Simulate Full Data (From Action DAG(s)) |
| simobs | Simulate Observed Data |
| sparseAdjMat.to.igraph | Convert Network from Sparse Adjacency Matrix into igraph Object |
| sparseAdjMat.to.NetInd | Convert Network from Sparse Adjacency Matrix into Network IDs Matrix |
| vecfun.add | Add Custom Vectorized Functions |
| vecfun.all.print | Print Names of All Vectorized Functions |
| vecfun.print | Print Names of Custom Vectorized Functions |
| vecfun.remove | Remove Custom Vectorized Functions |
| vecfun.reset | Reset Custom Vectorized Function List |