Causal Inference

BBH Causal Judgment refers to a framework for understanding causal relationships in data using Bayesian methods.

Causal tracing is a method used to identify and analyze cause-and-effect relationships in data or systems.

Counterfactuals refer to hypothetical scenarios exploring 'what if' questions about events that did not occur.

A Doubly Robust Estimator is a statistical method that combines two approaches to improve accuracy in estimating treatment effects.

An Instrumental Variable (IV) is a tool in statistical analysis used to estimate causal relationships when controlled experiments are not feasible.

Inverse Propensity Score is a statistical technique used in causal inference to adjust for selection bias in observational studies.

Logit Matching is a statistical method used to match treated and control groups based on predicted probabilities.