Measure Speaker's Impact Using Propensity Score Matching
RokuData Scientist · Technical ScreenLast updated
Evaluates causal inference for optional smart speaker ownership using propensity score matching and staggered adoption. Strong answers address self-selection, construct matched or weighted controls, validate balance and pre-trends, estimate ATT, and run placebo and sensitivity analyses.
Scenario
The company releases an optional smart speaker and wants to understand its effect on user engagement, but users self-select into purchasing.
Question
Without being able to run a forced A/B test, how would you measure the causal impact of owning the speaker on engagement? Describe your preferred design and why.
Hints
Discuss quasi-experiments: difference-in-differences, propensity-score matching, instrumental variables, pre-post checks.
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