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Explain Propensity Score Matching and Assess Covariate Balance

Last updated: Mar 29, 2026

Quick Overview

This question evaluates understanding of propensity score matching and causal inference, testing competency in propensity score concepts, matching rationale, essential assumptions (such as unconfoundedness and common support), and diagnostics for covariate balance.

Amazon

Aug 4, 2025, 10:55 AM

Data Scientist

Technical Screen

Statistics & Math

Propensity Score Matching (PSM)

Context

You have observational data with a binary treatment (T ∈ {0,1}), an outcome (Y), and a set of pre-treatment covariates (X). You want to estimate the causal effect of treatment on the outcome while adjusting for confounding.

Question

What is Propensity Score Matching (PSM)?
List its main assumptions.
Outline the implementation steps.
Describe how you would assess covariate balance after matching.

Hints: Discuss unconfoundedness, common support, caliper, and standardized mean differences (SMD).

Solution

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