Katkat
Back

Estimate Treatment Effects Using PSM, DiD, and DML Methods

AmazonData Scientist · Onsite
HardData ScientistOnsiteStatistics & Math

Last updated

Estimate Treatment Effects Using PSM, DiD, and DML Methods evaluates statistical assumptions, formulas, estimation strategy, uncertainty, edge cases, and interpretation in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Scenario

Marketing analytics team wants to measure the causal impact of campaigns.

Question

Explain how you would use Propensity Score Matching (PSM) and Difference-in-Differences (DiD) to estimate treatment effect. When is a synthetic control method preferable to DiD? Describe the Double Machine Learning (DML) framework for causal inference and why it helps with high-dimensional covariates.

Hints

Cover identification assumptions, overlap, parallel trends, cross-fitting, and robustness checks.