Model‐assisted estimators for time‐to‐event data from complex surveys

We develop model‐assisted estimators for complex survey data for the proportion of a population that experienced some event by a specified time t . Theory for the new estimators uses time‐to‐event models as the underlying framework but have both good model‐based and design‐based properties. The estimators are compared in a simulation to traditional survey estimation methods and are also applied to a study of nurses' health. The new estimators take advantage of covariates predictive of the event and reduce standard errors compared to conventional alternatives.