Propensity Score Weighting (IPW): Using Inverse Probability Weighting to Adjust for Confounding in Causal Inference
Introduction In real-world data analysis, figuring out cause-and-effect is often harder than spotting simple correlations. Observational data, unlike data from controlled experiments, is usually influenced by confounding variables that affect both who gets a treatment and what outcomes occur. This makes it tough to draw clear conclusions about causality. Propensity Score Weighting, or Inverse Probability … Read more