Explain Propensity Score Matching and Assess Covariate Balance

Q: Explain Propensity Score Matching and Assess Covariate Balance

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.

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Question

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).

Explain Propensity Score Matching and Assess Covariate Balance

Propensity Score Matching (PSM)

Context

Question

Solution

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Explain Propensity Score Matching and Assess Covariate Balance

Overview

Propensity Score Matching (PSM)

Context

Question

Solution

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