ABSTRACT
This chapter describes several methods for estimating variances of estimated totals and other statistics from complex surveys. It discusses the commonly used linearization method for calculating variances of estimators. The chapter presents random group and resampling methods for calculating variances of linear and nonlinear statistics. It shows that the calculation of generalized variance functions, and also describes constructing confidence intervals. Random group methods are easy to compute and explain but are unstable if a complex sample can only be split into a small number of groups. Resampling methods treat the sample as if it were itself a population; we take different samples from this new “population” and use the subsamples to estimate the variance. The jackknife method, like Balanced repeated replication, extends the random group method by allowing the replicate groups to overlap. K. M. Wolter summarizes some of the simulation studies; others are found in J. Kovar et al. and C. R. Rao et al.
