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Activity Number: 252 - SPEED:Improving Survey Data Quality with Multiple Data Sources, Administrative Data, and Nonresponse Bias Control, Part 2
Type: Contributed
Date/Time: Monday, July 29, 2019 : 2:00 PM to 2:45 PM
Sponsor: Survey Research Methods Section
Abstract #307633
Title: Oversampling Minority Populations in a Dual-Frame Telephone Survey
Author(s): Alexander Stubblefield* and Sixia Chen and Julie Stoner
Companies: University of Oklahoma Health Sciences Center and University of Oklahoma Health Sciences Center and University of Oklahoma Health Sciences Center
Keywords: Minority; Oversampling; Stratification; Telephone Survey

Previous studies have shown disparities in health conditions and behaviors among different ethnicity groups. Sampling design without considering oversampling certain minority populations such as American Indian or African American may not produce sufficient sample sizes for estimating health parameters for minority populations. Oversampling is one of the most common approaches that researchers use to achieve required precision levels for small domain estimation. However, it has not been rigorously investigated in dual-frame telephone survey settings. To take advantage of extra information for minority populations in Marketing Systems Group database, we propose a novel optimal oversampling strategy which minimizes the domain variance subject to total cost restriction or vice versa. We further extend the method to oversample multiple minorities simultaneously. Empirical study using a population-based community survey shows the benefits of our proposed methods compared with traditional methods in terms of statistical efficiency and cost balance.

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

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