jss_2006.RmdSandwich covariance matrix estimators are a popular tool in applied
regression modeling for performing inference that is robust to certain
types of model misspecification. Suitable implementations are available
in the R system for statistical computing for certain model fitting
functions only (in particular lm()), but not for other
standard regression functions, such as glm(),
nls(), or survreg().
Therefore, conceptual tools and their translation to computational tools in the package sandwich are discussed, enabling the computation of sandwich estimators in general parametric models. Object orientation can be achieved by providing a few extractor functions - most importantly for the empirical estimating functions - from which various types of sandwich estimators can be computed.
PDF: sandwich-OOP.pdf
Originally published as: Zeileis A (2006). “Object-Oriented Computation of Sandwich Estimators.” Journal of Statistical Software, 16(9), 1-16. doi:10.18637/jss.v016.i09.