Causal survival analysis under competing risks using longitudinal modified treatment policies

We present identification results and non-parametric locally efficient estimators that use flexible data-adaptive regression techniques to alleviate model misspecification bias, while retaining important asymptotic properties such as\(\sqrt{n}\)-consistency. We present an application to the estimation of the effect of the time-to-intubation on acute kidney injury amongst COVID-19 hospitalized patients, where death by other causes is taken to be the competing event.
Source: Lifetime Data Analysis - Category: Statistics Source Type: research