Applying the rescaling bootstrap under imputation for a multistage sampling design

Abstract In this paper, we propose a method that estimates the variance of an imputed estimator in multistage sampling design. The is based on rescaling bootstrap for introduced by Preston (Surv Methodol 35(2):227–234, 2009). his original version, resampling requires dataset includes only complete cases and no missing values. Thus, two modifications applying to nonresponse imputation. These are compared other Monte Carlo simulation study. results our study show proposed approaches superior and, many situations, produce valid estimators designs.