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Activity Number: 165 - SLDS CSpeed 2
Type: Contributed
Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistical Learning and Data Science
Abstract #317693
Title: Nonresponse Bias Study
Author(s): Forest Krueger* and Dhanapati Khatiwoda and Kyle Jeong
Companies: U.S. Census Bureau and U.S. Census Bureau and U.S. Census Bureau
Keywords: bias; nonresponse; r indicator; model; total quality response rate; unit response rate
Abstract:

In this study we have looked at traditional indicators of nonresponse bias like total quantity response rate (TQRR) and unit response rate (URR) and have now introduced a new bias indicator called the R-indicator. Studies have shown that there is not a direct link between nonresponse and nonresponse bias. Because of this relationship, additional measures to measure survey bias have to be used. In this study, an existing measure for the survey of the Quarterly Financial Report (QFR), TQRR, is looked at in conjunction with a new measure called the R-indicator. The R-indicator uses a model to determine variance of the response propensity to determine bias. These methods are explained and applied.


Authors who are presenting talks have a * after their name.

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