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Biometrika 2004 91(4):877-891; doi:10.1093/biomet/91.4.877
© 2004 by Biometrika Trust
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Adaptive cluster double sampling

Martín H. Félix-Medina1 and Steven K. Thompson2

1 Escuela de Ciencias Físico Matemáticas, Universidad Autónoma de Sinaloa, Ciudad Universitaria, Culiacán Sinaloa, México mhfelix{at}uas.uasnet.mx, 2 Department of Statistics, 326 Thomas Building, The Pennsylvania State University, University Park, Pennsylvania 16802-2111, U.S.A. skt{at}stat.psu.edu

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.

Key Words: Adaptive cluster sampling; Double sampling; Finite population; Horvitz–Thompson estimator; Multi-phase sampling; Regression estimator

Received May 2001. Revised March 2004.


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