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flag bad controls (mediator/collider/desc of Y) among a candidate set

Usage

bad_controls_in(dag, controls, exposure, outcome)

Arguments

dag

A dagitty DAG object.

controls

Character vector of variable names.

exposure

Character; exposure node name (X).

outcome

Character; outcome node name (Y).

Value

A character vector (possibly empty) containing the elements of controls that are identified as "bad controls".

This is essentially the inverse of pick_minimal_controls(), as it returns bad controls, rather than the minimal/canonical set of good controls

Examples

# Which variables in a formula are bad controls, given the DAG?
bad_controls_in(toy_dag, controls = c("M", "C", "Z"))
#> [1] "M" "C"