Estimating standardized parameters from generalized linear models

Although the traditional unrestricted ('non‐parametric') estimators of directly standardized rates and rate differences remain unbiased in sparse data, they tend to suffer from instability (low precision). As a result, many authors have proposed more precise estimators based on parametric models for the rates. This paper provides a general approach for constructing estimators of standardized parameters using generalized linear models, and shows that, in some common special cases, these model‐based ('smoothed') estimators can have an exceptionally simple form.