Package index • simDAG

DAGs

Create, manipulate and inspect DAGs

empty_dag(): Initialize an empty DAG object

node() node_td(): Create a node object for a DAG

network() network_td(): Create a network object for a DAG

net(): Specify Network Dependencies in a DAG

add_node() `+`(<DAG>): Add a DAG.node or a DAG.network object to a DAG object

plot(<DAG>): Plot a DAG object

as.igraph(<DAG>): Transform a DAG object into an igraph object

as.dagitty(<DAG>): Transform a DAG object into a dagitty object

do(): Pearls do-operator for DAG objects

dag2matrix(): Obtain a Adjacency Matrix from a DAG object

matrix2dag(): Obtain a DAG object from a Adjacency Matrix and a List of Node Types

dag_from_data(): Fills a partially specified DAG object with parameters estimated from reference data

Simulation

Simulate data from a DAG and manipulate or visualize the output

sim_from_dag(): Simulate Data from a DAG

sim_discrete_time(): Simulate Data from a DAG with Time-Dependent Variables

sim_n_datasets(): Simulate multiple datasets from a single DAG object

sim2data() as.data.table(<simDT>) as.data.frame(<simDT>): Transform sim_discrete_time output into the start-stop, long- or wide-format

plot(<simDT>): Plot a Flowchart for a Discrete-Time Simulation

Root nodes

Functions that can be used as root nodes

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

Child nodes

Functions that can be used as child nodes

node_gaussian(): Generate Data from a (Mixed) Linear Regression Model

node_binomial(): Generate Data from a (Mixed) Binomial Regression Model

node_conditional_prob(): Generate Data Using Conditional Probabilities

node_conditional_distr(): Generate Data by Sampling from Different Distributions based on Strata

node_multinomial(): Generate Data from a Multinomial Regression Model

node_poisson(): Generate Data from a (Mixed) Poisson Regression Model

node_negative_binomial(): Generate Data from a Negative Binomial Regression Model

node_zeroinfl(): Generate Data from a Zero-Inflated Count Model

node_identity(): Generate Data based on an expression

node_mixture(): Generate Data from a Mixture of Node Definitions

node_cox(): Generate Data from a Cox-Regression Model

node_aftreg() node_ahreg() node_ehreg() node_poreg() node_ypreg(): Generate Data from Parametric Survival Models

Time-dependent nodes

Functions that can only be used as time-dependent nodes

node_time_to_event(): Generate Data from repeated Bernoulli Trials in Discrete-Time Simulation

node_competing_events(): Generate Data with Multiple Mutually Exclusive Events in Discrete-Time Simulation

Misc

long2start_stop(): Transform a data.table in the long-format to a data.table in the start-stop format

simDAG-package: Simulate Data from a DAG and Associated Node Information