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Activity Number: 440
Type: Contributed
Date/Time: Wednesday, August 6, 2008 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #301807
Title: Optimized Whole-Sample Procedures vs. Traditional Draw-by-Draw Procedures
Author(s): Sun-Woong Kim*+ and Steven G. Heeringa and Sung-Joon Hong and Peter S. Solenberger
Companies: Dongguk University and Institute for Social Research and Dongguk University and Institute for Social Research
Address: Department of Statistics, Seoul, International, 100-715, South Korea
Keywords: Superpopulation model ; Expected variance ; Joint probabilities
Abstract:

Kim, Heeringa, and Solenberger (2006) suggested two model-based sampling methods for reducing the variance of the Horvitz-Thompson (1952) estimator. Their methods are whole sample procedures based on optimization theory under a superpopulation model. With respect to the sample selection probabilities, we theoretically present the differences between those procedures and popular draw-by-draw procedures such as sampling methods of Mizuno (1952), Brewer (1963), and Murthy (1957), when the sample size is two, which is a common situation in nationwide samples with many strata. We also compare the efficiencies between them for natural populations in the published literature. It appears that the methods of Kim, Heeringa and Solenberger (2006) may be preferable to those draw-by-draw procedures in many situations.

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