Using Imputation Techniques to Evaluate Stopping Rules in Adaptive Survey Designs

35 Pages Posted: 3 Apr 2015

Date Written: September 1, 2014

Abstract

Adaptive Design methods for social surveys utilize the information from the data as it is collected to make decisions about the sampling design. In some cases, the decision is either to continue or stop the data collection. We evaluate this decision by proposing measures to compare the collected data with follow-up samples. The options are assessed by imputation of the nonrespondents under different missingness scenarios, including Missing Not at Random. The variation in the utility measures is compared to the cost induced by the follow-up sample sizes. We apply the proposed method to the 2007 U.S. Census of Manufacturers.

Suggested Citation

Paiva, Thais and Reiter, Jerome, Using Imputation Techniques to Evaluate Stopping Rules in Adaptive Survey Designs (September 1, 2014). US Census Bureau Center for Economic Studies Paper No. CES-WP- 14-40, Available at SSRN: https://ssrn.com/abstract=2572682 or http://dx.doi.org/10.2139/ssrn.2572682

Thais Paiva (Contact Author)

Duke University

100 Fuqua Drive
Durham, NC 27708-0204
United States

Jerome Reiter

Duke University ( email )

100 Fuqua Drive
Durham, NC 27708-0204
United States

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