This article reviews the applications of three resampling methods, the jackknife, the balanced repeated replication, and the bootstrap, in sample surveys. The sampling design under consideration is a stratified multistage sampling design. We discuss the implementation of the resampling methods; for example, the construction of balanced repeated replications and approximated balanced repeated replication estimators; four modified bootstrap algorithms to generate bootstrap samples; and three different ways of applying the resampling methods in the presence of imputed missing values. Asymptotic properties of the resampling estimators are discussed for two types of important survey estimators, functions of weighted averages and sample quantiles.