Bootstrap Variance Estimation for Rejective Sampling

• 成果类型: Article
• 署名作者: Fuller, Wayne A.; Legg, Jason C.; Li, Yang
• 署名单位: Iowa State University; Amgen; University of Minnesota System; University of Minnesota Duluth
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2016.1222285
• 发表日期: 2017
• 页码: 1562-1570
• 关键词: complex survey data

摘要

Replication procedures have proven useful for variance estimation for large scale complex surveys. As an extension of bootstrap procedures to rejective samples, we define a bootstrap sample that is a rejective, unequal probability, replacement sample selected from the original sample. A modification of the bootstrap with improved performance is suggested for stratified samples with small stratum sizes. Simulations for Poisson and stratified rejective samples support the use of replicates in estimating the variance of the regression estimator for rejective samples.