R: Simulate Data from a (Time-Dependent) Causal DAG

# Simulate Data from a (Time-Dependent) Causal DAG

## Documentation for package ‘simDAG’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

simDAG-package | Simulate Data from a DAG and Associated Node Information
+.DAG | Add a 'DAG.node' or a 'DAG.network' object to a 'DAG' object
add_node | Add a 'DAG.node' or a 'DAG.network' object to a 'DAG' object
as.dagitty.DAG | Transform a 'DAG' object into a 'dagitty' object
as.data.frame.simDT | Transform 'sim_discrete_time' output into the start-stop, long- or wide-format
as.data.table.simDT | Transform 'sim_discrete_time' output into the start-stop, long- or wide-format
as.igraph.DAG | Transform a 'DAG' object into an 'igraph' object
as_tidy_dagitty.DAG | Transform a 'DAG' object into a 'tidy_dagitty' object
dag2matrix | Obtain a Adjacency Matrix from a 'DAG' object
dag_from_data | Fills a partially specified 'DAG' object with parameters estimated from reference data
do | Pearls do-operator for 'DAG' objects
empty_dag | Initialize an empty 'DAG' object
long2start_stop | Transform a 'data.table' in the long-format to a 'data.table' in the start-stop format
matrix2dag | Obtain a 'DAG' object from a Adjacency Matrix and a List of Node Types
net | Specify Network Dependencies in a 'DAG'
network | Create a network object for a 'DAG'
network_td | Create a network object for a 'DAG'
node | Create a node object for a 'DAG'
node_aalen | Generate Data from an Aalen Additive Hazards Model
node_aftreg | Generate Data from Parametric Survival Models
node_ahreg | Generate Data from Parametric Survival Models
node_binomial | Generate Data from a (Mixed) Binomial Regression Model
node_competing_events | Generate Data with Multiple Mutually Exclusive Events in Discrete-Time Simulation
node_conditional_distr | Generate Data by Sampling from Different Distributions based on Strata
node_conditional_prob | Generate Data Using Conditional Probabilities
node_cox | Generate Data from a Cox-Regression Model
node_ehreg | Generate Data from Parametric Survival Models
node_gaussian | Generate Data from a (Mixed) Linear Regression Model
node_identity | Generate Data based on an expression
node_mixture | Generate Data from a Mixture of Node Definitions
node_multinomial | Generate Data from a Multinomial Regression Model
node_negative_binomial | Generate Data from a Negative Binomial Regression Model
node_next_time | Generate the Next Time of an Event in Discrete-Event Simulation
node_poisson | Generate Data from a (Mixed) Poisson Regression Model
node_polr | Generate Data from an Ordered Logistic or Probit Regression
node_poreg | Generate Data from Parametric Survival Models
node_rsurv | Generate Data from Parametric Survival Models
node_td | Create a node object for a 'DAG'
node_time_to_event | Generate Data from repeated Bernoulli Trials in Discrete-Time Simulation
node_ypreg | Generate Data from Parametric Survival Models
node_zeroinfl | Generate Data from a Zero-Inflated Count Model
plot.DAG | Plot a 'DAG' object
plot.simDT | Plot a Flowchart for a Discrete-Time Simulation
rbernoulli | Generate Random Draws from a Bernoulli Distribution
rcategorical | Generate Random Draws from a Discrete Set of Labels with Associated Probabilities
rconstant | Use a single constant value for a root node
rsample | Sample values from a given vector
rtexp | Generate Data from a left-truncated exponential distribution
sim2data | Transform 'sim_discrete_time' output into the start-stop, long- or wide-format
sim_discrete_event | Simulate Data from a 'DAG' with Time-Dependent Variables in Continuous Time
sim_discrete_time | Simulate Data from a 'DAG' with Time-Dependent Variables in Discrete Time
sim_from_dag | Simulate Data from a 'DAG'
sim_n_datasets | Simulate multiple datasets from a single 'DAG' object