A survey of bootstrap methods in finite population sampling
Authors:
- Zeinab MashreghiZMZeinab Mashreghi
- David HazizaDHDavid Haziza
- Christian LégerCLChristian Léger
Open Access
- 1 January 2016
- journal article
- Published by Institute of Mathematical Statistics in Statistics Surveys
- Vol. 10 (none) , 1-52
Abstract
We review bootstrap methods in the context of survey data where the effect of the sampling design on the variability of estimators has to be taken into account. We present the methods in a unified way by classifying them in three classes: pseudo-population, direct, and survey weights methods. We cover variance estimation and the construction of confidence intervals for stratified simple random sampling as well as some unequal probability sampling designs. We also address the problem of variance estimation in presence of imputation to compensate for item non-response.Keywords
This publication has 56 references indexed in Scilit:
- Variance Estimation for Survey Data with Composite Imputation and Nonnegligible Sampling FractionsJournal of the American Statistical Association, 1999
- Bootstrap for Imputed Survey DataJournal of the American Statistical Association, 1996
- On Balanced Half-Sample Variance Estimation in Stratified Random SamplingJournal of the American Statistical Association, 1996
- Bootstrap Methods for Finite PopulationsJournal of the American Statistical Association, 1994
- A Resampling Procedure for Complex Survey DataJournal of the American Statistical Association, 1992
- Resampling Inference with Complex Survey DataJournal of the American Statistical Association, 1988
- Inference from Stratified Samples: Second-Order Analysis of Three Methods for Nonlinear StatisticsJournal of the American Statistical Association, 1985
- Survey Design under the Regression Superpopulation ModelJournal of the American Statistical Association, 1982
- Constructing Orthogonal Replications for Variance EstimationJournal of the American Statistical Association, 1975
- A Generalization of Sampling Without Replacement from a Finite UniverseJournal of the American Statistical Association, 1952