Struct BackdoorCriterion 

pub struct BackdoorCriterion {
    pub graph: CausalGraph,
}

Checks whether a set of variables satisfies the backdoor criterion for identifying the causal effect of treatment on outcome.

The backdoor criterion holds if:

1. No variable in adjustment_set is a descendant of treatment.
2. adjustment_set blocks all backdoor paths from treatment to outcome.

Fields

graph: CausalGraph

The causal graph.

Implementations

impl BackdoorCriterion

pub fn new(graph: CausalGraph) -> Self

Create a new backdoor criterion checker.

pub fn check( &self, treatment: usize, outcome: usize, adjustment_set: &[usize], ) -> bool

Check if adjustment_set satisfies the backdoor criterion for the causal effect of treatment on outcome.

Returns true if the criterion is satisfied.

pub fn adjusted_effect( data_x: &[f64], data_y: &[f64], data_z: &[f64], x_val: f64, _tolerance: f64, ) -> f64

Compute the backdoor-adjusted causal effect estimate from observational data.

Uses the adjustment formula: E[Y|do(X=x)] = Σ_z E[Y|X=x, Z=z] * P(Z=z)

This simplified version takes pre-computed conditional means.

Arguments

• data_x — treatment values
• data_y — outcome values
• data_z — confounder values (single confounder for simplicity)
• x_val — the intervention value

Trait Implementations

impl Clone for BackdoorCriterion

fn clone(&self) -> BackdoorCriterion

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for BackdoorCriterion

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.