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Activity Number:
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298
- SPEED: Innovations in Survey Sampling Designs: Administrative Data, Record Linkage, Non-Probability Samples, and More
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
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Sponsor:
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Survey Research Methods Section
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Abstract #330708
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Presentation
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Title:
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Samples, Unite! Understanding the Consequences of Combining Probability and Non-Probability Samples When Linking Records Is Difficult
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Author(s):
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Benjamin Williams*
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Companies:
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Southern Methodist University
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Keywords:
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Record Linkage;
Non Probability Sampling;
Sampling;
Combining samples;
Biometrics;
Matching
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Abstract:
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In this paper, combining a large non-probability sample with a smaller probability sample when it is difficult to correctly link records from the two samples is examined. To estimate the total number of units in the population a new method is proposed that treats the non-probability sample as its own stratum. This method is compared to current techniques under various settings of sample parameters and confidence in the matching process. I also examine the effect that record linkage has on the variance of the estimators. This work is then tested on a real world example: the estimation of total fish removed from the Gulf of Mexico by recreational anglers. NOAA is implementing a new technique for gathering fishing statistics in the Gulf of Mexico that involves captains voluntarily self-reporting catch statistics via electronic tablets alongside a random dockside intercept sample. In order to combine the two data sources it is necessary to combine a probability sample (dockside intercept) with a non-probability sample (self-reports). Accurately matching anglers who both self-report and appear in the dockside sample is challenging, resulting in a useful test case.
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Authors who are presenting talks have a * after their name.
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