A Comparison of Existing Bootstrap Algorithms for Multi-Stage Sampling Designs

Multi-stage sampling designs are often used in household surveys because a frame of elements may not be available or for cost considerations when data collection involves face-to-face interviews. In this context, variance estimation is complex task as it relies on the availability second-order inclusion probabilities at each stage. To cope with issue, several bootstrap algorithms have been proposed literature context two-stage design. paper, we describe some these and compare them empirically terms bias, stability, coverage probability.