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Activity Number: 118
Type: Topic Contributed
Date/Time: Monday, August 4, 2014 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #311620
Title: Multivariate Sample Design Optimization for NHTSA's New National Automotive Sampling System
Author(s): Yumiko Sugawara*+ and Barnali Das and Rui Jiao and James Green
Companies: Westat and Westat and Westat and Westat
Keywords: Multivariate sample design ; optimization

NHTSA's new National Automotive Sampling System (NASS) is expected to address a large number of research questions and analytic objectives, and therefore requires a multi-purpose study and sample design. In addition, the new NASS consists of multiple modules, with future funding levels and precision requirements unknown and subject to change for any given module. A multivariate sample design optimization system was designed and built for NHTSA to address these design requirements, parameters and constraints. The system offers two options: A) Minimize cost subject to variance constraints; B) Minimize a weighted sum of variances subject to cost constraints. This paper presents the development and architecture of the sample design optimization system, a description of its outputs, the iterative process of reviewing those outputs, and the ability to modify design parameters and constraints.

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