4.3 Article

Effects of Address Coverage Enhancement on Estimates from Address-Based Sampling Studies

Journal

JOURNAL OF SURVEY STATISTICS AND METHODOLOGY
Volume 11, Issue 2, Pages 340-366

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/jssam/smab032

Keywords

Address-based sampling; Address Coverage Enhancement; Noncoverage bias; Sampling frame coverage

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This article investigates the Address Coverage Enhancement (ACE) procedure, which supplements address-based sampling (ABS) frames with addresses not found on the frame. The study finds that the noncoverage bias is likely minimal, as the Computerized Delivery Sequence file coverage rate is high.
For over a decade, address-based sampling (ABS) frames have often been used to draw samples for multistage area sample surveys in lieu of traditionally listed (or enumerated) address frames. However, it is well known that the use of ABS frames for face-to-face surveys suffer from undercoverage due to, for example, households that receive mail via a PO Box rather than being delivered to the household's street address. Undercoverage of ABS frames has typically been more prominent in rural areas but can also occur in urban areas where recent construction of households has taken place. Procedures have been developed to supplement ABS frames to address this undercoverage. In this article, we investigate a procedure called Address Coverage Enhancement (ACE) that supplements the ABS frame with addresses not found on the frame, and the resulting effects the addresses added to the sample through ACE have on estimates. Weighted estimates from two studies, the Population Assessment of Tobacco and Health Study and the 2017 US Program for the International Assessment of Adult Competencies, are calculated with and without supplemental addresses. Estimates are then calculated to assess if poststratifying analysis weights to control for urbanicity at the person level brings estimates closer to estimates from the supplemented frame. Our findings show that the noncoverage bias was likely minimal across both studies for a range of estimates. The main reason is because the Computerized Delivery Sequence file coverage rate is high, and when the coverage rate is high, only very large differences between the covered and not covered will result in meaningful bias.

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