Adaptive cluster double sampling
成果类型：
Article
署名作者：
Félix-Medina, MH; Thompson, SK
署名单位：
Universidad Autonoma de Sinaloa; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/91.4.877
发表日期：
2004
页码：
877891
关键词：
摘要：
We present a multi-phase variant of adaptive cluster sampling which allows the sampler to control the number of measurements of the variable of interest. A first-phase sample is selected using an adaptive cluster sampling design based on an inexpensive auxiliary variable associated with the survey variable. Then the network structure of the adaptive cluster sample is used to select an ordinary one-phase or two-phase subsample of units and the values of the survey variable associated with those units are recorded. The population mean is estimated by either a regression-type estimator or a Horvitz-Thompson-type estimator. The results of a simulation study show good performance of the proposed design, and suggest that in many real situations this design might be preferred to the ordinary adaptive cluster sampling design.