JSM 2005 - Toronto

Abstract #303334

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Activity Number: 527
Type: Contributed
Date/Time: Thursday, August 11, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods
Abstract - #303334
Title: An Evaluation of Synthetic Small-area Census Coverage Error Using a Random Effects Model
Author(s): Donald Malec*+ and Jerry Maples
Companies: U.S. Census Bureau/National Institute of Standards and Technology and U.S. Census Bureau
Address: 4700 Silver Hill Road, Washington, DC, 20233, United States
Keywords:
Abstract:

The synthetic estimation approach currently in use for estimating net U.S. Census coverage of small areas from the 2000 Census Revision II is discussed in this paper. First, a model is used which reproduces the synthetic estimate components. Second, the model is enlarged to include random effects at the small-area level. Keeping all of the fixed effects that characterize the synthetic model produces an extremely large, saturated random effects model. Hence, we selectively reduce the random effects model with an aim toward keeping all fixed effects in order to fairly evaluate the synthetic model. A super-population model was used for the trivariate outcome of erroneous enumeration rate, census omission rate, and data-defined census return rate. A major hurdle in this project was development of defensible input data for the small areas due to the large number of effects in the synthetic model that render simple design-based estimates for small areas crossed with poststrata, mostly not useable. For this initial approach, the small areas were the 540 local census offices. Bayesian methods are employed to evaluate these models.

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