select_controls: Select Covariate Adjustment Sets from Data

In theorytools: FAIR Theory Construction

Select Covariate Adjustment Sets from Data

Description

Wraps adjustmentSets to construct a dataset with covariates that (asymptotically) allow unbiased estimation of causal effects from observational data.

Usage

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

Arguments

x	An input graph of class dagitty.
data	A data.frame or object coercible by as.data.frame().
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}')
df <- data.frame(x = rnorm(10), y = rnorm(10))
df1 <- select_controls(dag, df, exposure = "x", outcome = "y")
class(df1) == "data.frame"
df2 <- select_controls(dag, df, exposure = "x", outcome = "y", which_set = "sample")
class(df2) == "data.frame"
lst1 <- select_controls(dag, df, exposure = "x", outcome = "y", which_set = "all")
class(lst1) == "list"

theorytools documentation built on Aug. 8, 2025, 6:43 p.m.