Variance estimation techniques for nonlinear statistics, such as ratios and regression and correlation coefficients, and functionals, such as quantiles, are reviewed in the context of sampling from stratified populations. In particular, resampling methods such as the bootstrap, the jackknife, and balanced repeated replication are compared with the traditional linearization method for nonlinear statistics and a method based on Woodruff's confidence intervals for the quantiles. Results of empirical studies are presented on the bias and stability of these variance estimators and on confidence‐interval coverage probabilities and lengths. Copyright

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Keywords balanced repeated replication, confidence intervals, Jackknife, medians, nonlinear statistics, stratified sampling, variance estimation
Persistent URL dx.doi.org/10.2307/3315214
Journal Canadian Journal of Statistics
Citation
Kovar, J.G., Rao, J.N.K, & Wu, C.F.J. (1988). Bootstrap and other methods to measure errors in survey estimates. Canadian Journal of Statistics, 16(1 S), 25–45. doi:10.2307/3315214