Estimation in multiple-frame surveys
成果类型：
Article
署名作者：
Lohr, Sharon; Rao, J. N. K.
署名单位：
Arizona State University; Arizona State University-Tempe; Carleton University
刊物名称：
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
ISSN/ISSBN：
0162-1459
DOI：
10.1198/016214506000000195
发表日期：
2006
页码：
1019-1030
关键词：
摘要：
Multiple-frame surveys are commonly used to decrease costs of sampling or to reduce undercoverage that could occur if only one sampling frame were used. We describe potential uses and examples of multiple-frame surveys. We then derive optimal linear estimators and pseudomaximum likelihood estimators for the population total when samples are taken independently from each frame using probability sampling designs. We explore the properties of these estimators theoretically and through a simulation study. We also derive variance estimators and discuss some practical problems that may be encountered in multiple-frame surveys.