Simulating Longitudinal Data with Causal Inference Applications

---

Documentation for package ‘simcausal’ version 0.5.6

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

+.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