Adjusting for unmeasured confounding using validation data: Simplified two‐stage calibration for survival and dichotomous outcomes

In epidemiology, one typically wants to estimate the risk of an outcome associated with an exposure after adjusting for confounders. Sometimes, outcome and exposure and maybe some confounders are available in a large data set, whereas some important confounders are only available in a validation data set that is typically a subset of the main data set. A generally applicable method in this situation is the two‐stage calibration (TSC) method. We...