We present results from a large-scale, randomized field experiment on Spotify testing the
effect of personalized recommendations on consumption diversity. In the experiment, both …

Sharp instruments for classifying compliers and generalizing causal effects Page 1 The Annals
of Statistics 2020, Vol. 48, No. 4, 2008–2030 https://doi.org/10.1214/19-AOS1874 © Institute of …

A randomized trial allows estimation of the causal effect of an intervention compared to a
control in the overall population and in subpopulations defined by baseline characteristics …

Reputation systems are used by nearly every digital marketplace, but designs vary and the
effects of these designs are not well understood. We use a large-scale experiment on Airbnb …

Causal inference methods are gaining increasing prominence in pharmaceutical drug
development in light of the recently published addendum on estimands and sensitivity …

When an exposure of interest is confounded by unmeasured factors, an instrumental
variable (IV) can be used to identify and estimate certain causal contrasts. Identification of …

Causal inference concerns not only the average effect of the treatment on the outcome but
also the underlying mechanism through an intermediate variable of interest. Principal …

The ICH E9 (R1) addendum (2019) proposed principal stratification (PS) as one of five
strategies for dealing with intercurrent events. Therefore, understanding the strengths …

Post-treatment variables often complicate causal inference. They appear in many scientific
problems, including noncompliance, truncation by death, mediation, and surrogate endpoint …

In causal mediation analysis, the definitions of the natural direct and indirect effects involve
potential outcomes that can never be observed, so-called a priori counterfactuals. This …