On the Variances of Asymptotically Normal Estimators from Complex Surveys

Abstract

Summary The problem of specifying and estimating the variance of estimated parameters based on complex sample designs from finite populations is considered. The results of this paper are particularly useful when the parameter estimators cannot be defined explicitly as a function of other statistics from the sample. It is shown how these results can be applied to linear regression, logistic regression and log linear contingency table models. An example of the application of the technique to the Canada Health Survey is given.