On Sun, 24 Dec 2006, John Fox wrote: > If I remember Freedman's recent paper correctly, he argues that sandwich > variance estimator, though problematic in general, is not problematic in the > case that White described -- an otherwise correctly specified linear model > with heteroscedasticity estimated by least-squares.
More generally, sandwich-type estimators are valid (i.e., estimate the right quantity, although not necessarily precisely, as Frank pointed out) in situations where the estimating functions are correctly specified but remaining aspets of the likelihood (not captured in the estimating functions) are potentially not. In linear models, it is easy to see what this means: the mean function has to be correctly specified (i.e., the errors have zero mean) but the correlation structure of the errors (i.e., their (co-)variances) might differ from the usual assumptions. In GLMs, in particular logistic regression, it is much more difficult to see against which types of misspecification sandwich-based inference is robust. Freedman's paper stresses the point that many model misspecifications also imply misspecified estimating functions (and in his example this is rather obvious) so that consequently the sandwich-type estimators estimate the wrong quantity. Best wishes, Z ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.