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Activity Number: 48 - Bayesian Adaptive Survey Designs
Type: Invited
Date/Time: Sunday, July 30, 2017 : 4:00 PM to 5:50 PM
Sponsor: Survey Research Methods Section
Abstract #322092
Title: More Information Is Better! Where Do We Get it and How Do We Use It?
Author(s): Stephanie Michelle Coffey*
Companies: U.S. Census Bureau; JPSM University of Maryland
Keywords: data collection ; adaptive design ; propensity models ; bayesian methods

One factor that is often overlooked in dynamic adaptive designs is whether a certain data collection strategy is "worth it", with respect to reaching data collection goals. Ideally, we would not send that expensive field interviewer to attempt a case that will not respond to either a telephone attempt or a personal visit, as resources could be better spent on other similar cases. Alternatively, perhaps a small incentive would convince a sample individual to respond. To use this type of information, we need to look at the response propensity of a case (and how it is affected by different data collection features) in addition to its value to the data collection goal. This is difficult, as we do not know in advance the effect of different combinations of features on survey response - we cannot tell the future. As a result we rely on models, but early in data collection, when a decision could have a large impact at reducing cost and burden, response propensities are often unreliable, shown by Wagner. This talk will illustrate how poor estimates of response propensity can affect data collection decisions, the potential benefits of external information, and how to integrate that data.

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

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