no code implementations • 17 Feb 2021 • Kristina Gligorić, Ryen W. White, Emre Kiciman, Eric Horvitz, Arnaud Chiolero, Robert West
To estimate causal effects from the passively observed log data, we control confounds in a matched quasi-experimental design: we identify focal users who at first do not have any regular eating partners but then start eating with a fixed partner regularly, and we match focal users into comparison pairs such that paired users are nearly identical with respect to covariates measured before acquiring the partner, where the two focal users' new eating partners diverge in the healthiness of their respective food choice.