Skip to contents

Prune DAG Based on Adjustment Sets

prune_dag.Rd

Wraps adjustmentSets to construct a pruned DAG which only includes covariates that (asymptotically) allow unbiased estimation of the causal effects of interest.

Usage

prune_dag(
  x,
  exposure = NULL,
  outcome = NULL,
  which_set = c("first", "sample", "all"),
  ...
)

Arguments

x

An input graph of class dagitty.

exposure

Atomic character, name of the exposure variable.

outcome

Atomic character, name of the outcome variable.

which_set

Atomic character, indicating which set of covariates to select in case there are multiple. Valid choices are in c("first", "sample", "all"), see Value.

...

Other arguments passed to adjustmentSets

Value

If which_set = "all", returns a list of data.frames to allow for sensitivity analyses. Otherwise, returns a data.frame.

See also

adjustmentSets

Examples

dag <- dagitty::dagitty('dag {x -> y}')
prune_dag(dag, exposure = "x", outcome = "y")
#> dag {
#> x
#> y
#> x -> y
#> }