A jackknife variance estimator for unequal probability sampling

• 成果类型: Article
• 署名作者: Berger, YG; Skinner, CJ
• 署名单位: University of Southampton
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/j.1467-9868.2005.00489.x
• 发表日期: 2005
• 页码: 79-89
• 关键词: varying probabilities; stratified samples; ASYMPTOTIC THEORY; inference; Consistency

摘要

The jackknife method is often used for variance estimation in sample surveys but has only been developed for a limited class of sampling designs. We propose a jackknife variance estimator which is defined for any without-replacement unequal probability sampling design. We demonstrate design consistency of this estimator for a broad class of point estimators. A Monte Carlo study shows how the proposed estimator may improve on existing estimators.