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Activity Number:
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126
- Interpreting Nonprobability Samples: Discoveries and Challenges
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Type:
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Topic-Contributed
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Date/Time:
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Monday, August 9, 2021 : 1:30 PM to 3:20 PM
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Sponsor:
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Survey Research Methods Section
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Abstract #317478
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Title:
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Creating Statistically-Defensible Calibrated Weights for a Blended Sample and Measuring the Accuracy of the Resulting Estimates
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Author(s):
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Phillip Kott* and Jamie Ridenhour
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Companies:
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RTI International and RTI International
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Keywords:
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Selection model;
Output model;
calibration equation;
double protection;
logit function;
WTADJX
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Abstract:
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We show how calibration weighting can be employed to combine a probability and a nonprobability sample of the same population in a statistically-defensible manner. This is done by assuming the probability of a population element being included in the nonprobability sample can be modeled as a logit function of variables known for all members of both samples. Estimating these probabilities for the members of the nonprobability sample with a calibration equation and treating their inverses as quasi-probability weights is a key to creating composite weights for the blended sample. The WTADJX procedure in SUDAAN® is employed to generate those weights and then measure the standard errors or resulting estimated means and totals.
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Authors who are presenting talks have a * after their name.
