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. Copyrigh
Consider a finite population from which the stratified sample with simple random sample without repl...
In complex survey sampling every population unit is assigned a specific probability to be included ...
No Abstract.Global Journal of Pure and Applied Sciences Vol. 14 (2) 2008 pp. 217-22
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
This article discusses some resampling techniques that have found widespread application in survey ...
Application of the bootstrap in sample survey settings presents considerable practical and conceptua...
In survey sampling, accuracy of point estimates are assessed using variance estimates. Variance esti...
Two bootstrapping or resampling strategies were investigated to determine their applicability to est...
Several features of sample surveys generally render inapplicable the st and ard explicit forms of va...
The Bootstrap resampling method is introduced to the nonlinear theory for solving the precision esti...
In this article, I discuss the main approaches to resampling variance estimation in complex survey d...
In large multipurpose surveys, it is common to select the sample systematically proportional to some...
We show that the coverage error of confidence intervals and level error of hypothesis tests for popu...
Abstract: The bootstrap method works for both smooth and nonsmooth statistics, and replaces theoreti...
This report compares the bootstrapping to jacknifing statistical procedures in terms in bias, confid...
Consider a finite population from which the stratified sample with simple random sample without repl...
In complex survey sampling every population unit is assigned a specific probability to be included ...
No Abstract.Global Journal of Pure and Applied Sciences Vol. 14 (2) 2008 pp. 217-22
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
This article discusses some resampling techniques that have found widespread application in survey ...
Application of the bootstrap in sample survey settings presents considerable practical and conceptua...
In survey sampling, accuracy of point estimates are assessed using variance estimates. Variance esti...
Two bootstrapping or resampling strategies were investigated to determine their applicability to est...
Several features of sample surveys generally render inapplicable the st and ard explicit forms of va...
The Bootstrap resampling method is introduced to the nonlinear theory for solving the precision esti...
In this article, I discuss the main approaches to resampling variance estimation in complex survey d...
In large multipurpose surveys, it is common to select the sample systematically proportional to some...
We show that the coverage error of confidence intervals and level error of hypothesis tests for popu...
Abstract: The bootstrap method works for both smooth and nonsmooth statistics, and replaces theoreti...
This report compares the bootstrapping to jacknifing statistical procedures in terms in bias, confid...
Consider a finite population from which the stratified sample with simple random sample without repl...
In complex survey sampling every population unit is assigned a specific probability to be included ...
No Abstract.Global Journal of Pure and Applied Sciences Vol. 14 (2) 2008 pp. 217-22