Estimate the identified effect from data

Usage

morie_dag_estimate(
  dag,
  data,
  method = c("backdoor.aipw", "backdoor.linear", "backdoor.dml")
)

Arguments

dag: A morie_dag.
data: Data frame containing the observed nodes.
method: "backdoor.aipw" (default), "backdoor.linear", or "backdoor.dml" — all native estimators.

Value

The chosen estimator's result list, plus adjustment_set and estimand.

Examples

set.seed(1)
z <- rnorm(400); x <- rbinom(400, 1, plogis(z))
y <- 0.8 * x + z + rnorm(400)
df <- data.frame(z = z, x = x, y = y)
g <- morie_dag(c("z -> x", "z -> y", "x -> y"), "x", "y")
morie_dag_estimate(g, df, method = "backdoor.linear")
#> $ate
#> [1] 0.8599143
#> 
#> $se
#> [1] 0.1218017
#> 
#> $ci_lower
#> [1] 0.6211829
#> 
#> $ci_upper
#> [1] 1.098646
#> 
#> $n
#> [1] 400
#> 
#> $estimand
#> [1] "backdoor"
#> 
#> $adjustment_set
#> [1] "z"
#> 
#> $method
#> [1] "backdoor.linear (rmorie native)"
#>