The problem of the estimation of the design-variance and the design-MSE of different estimators and predictors is considered. Bootstrap algorithms applicable to complex sampling designs are used. A generalisation of the bootstrap procedure studied by Quatember (2014) is proposed. In most of the cases considered in our simulation study it leads to more accurate estimates (or to very similar ones in remaining cases) of the designMSE and the design-variance compared with the original algorithm and its other counteparts
In complex designs, classical bootstrap methods result in a biased variance estimator when the samp...
In this paper, we propose a method that estimates the variance of an imputed estimator in a multista...
This tutorial considers some very general procedures for analysing the results of a simulation exper...
This article provides general procedures for obtaining unbiased estimates of variance components for...
In complex survey sampling every population unit is assigned a specific probability to be included ...
Whether survey data are being used for estimating descriptive statistics about the population from w...
Estimating standard errors of estimated variance components has long been a challen-ging task in gen...
This Phd deals with Bootstrap methods for finite population sampling. The first chapter introduces s...
The paper considers the use of the bootstrap method to improve the determination of confidence inter...
The Rao-Wu bootstrap variance estimation method is frequently used at Statistics Canada. It is simpl...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
© 2017 The Econometric Society The bootstrap is a convenient tool for calculating standard errors of...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results un...
ObjectiveThe purpose of this study is to compare the performance of the four estimation methods (tra...
In complex designs, classical bootstrap methods result in a biased variance estimator when the samp...
In this paper, we propose a method that estimates the variance of an imputed estimator in a multista...
This tutorial considers some very general procedures for analysing the results of a simulation exper...
This article provides general procedures for obtaining unbiased estimates of variance components for...
In complex survey sampling every population unit is assigned a specific probability to be included ...
Whether survey data are being used for estimating descriptive statistics about the population from w...
Estimating standard errors of estimated variance components has long been a challen-ging task in gen...
This Phd deals with Bootstrap methods for finite population sampling. The first chapter introduces s...
The paper considers the use of the bootstrap method to improve the determination of confidence inter...
The Rao-Wu bootstrap variance estimation method is frequently used at Statistics Canada. It is simpl...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
© 2017 The Econometric Society The bootstrap is a convenient tool for calculating standard errors of...
For estimation of parameters of a multi-level model fitted to hierarchical survey data, the standard...
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results un...
ObjectiveThe purpose of this study is to compare the performance of the four estimation methods (tra...
In complex designs, classical bootstrap methods result in a biased variance estimator when the samp...
In this paper, we propose a method that estimates the variance of an imputed estimator in a multista...
This tutorial considers some very general procedures for analysing the results of a simulation exper...