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Variables appended to ABS frames: Has their data quality improved?

Shelley Roth¹, Andrew Caporaso¹, Jill DeMatteis¹

¹Westat, Rockville, Maryland, United States of America.

|November 2, 2022

Summary

This summary is machine-generated.

Address-based sampling (ABS) data quality was evaluated for demographic and socioeconomic variables. Select appended variables, like Hispanic origin and age 65+, are useful for oversampling, but others are not.

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Area of Science:

Survey Methodology
Statistical Sampling
Data Quality Assessment

Background:

Address-based sampling (ABS) is a leading method for U.S. household surveys via mail, phone, or web.
ABS frames allow appending external data for enhanced survey design and analysis.
The quality and completeness of appended data vary significantly across sources.

Purpose of the Study:

To assess the data quality of demographic and socioeconomic variables appended to recent ABS samples from a specific vendor.
To evaluate the utility of these appended variables for survey sample design, particularly for oversampling specific subgroups.
To compare appended data quality with respondent-reported data from two large ABS household surveys.

Main Methods:

Evaluated completeness of appended demographic and socioeconomic data for ABS samples.
Assessed concordance between appended data and respondent-reported data in online and mail-only ABS surveys.
Examined the effectiveness of appended variables for targeted oversampling strategies.

Main Results:

Completeness and quality of some appended variables have improved.
Variables such as Hispanic origin, Hispanic surname, and presence of individuals aged 65+ demonstrate utility for efficient oversampling.
Appended variables were found unsuitable for oversampling home tenure, educational attainment (high school or less), low income, households with children, specific adult age groups, or by the number of adults.

Conclusions:

Certain appended variables in ABS frames are now of sufficient quality for targeted oversampling of specific demographic groups.
The utility of appended data for oversampling is variable and depends heavily on the specific subgroup and variable.
Researchers should carefully assess data quality before relying on appended variables for complex sample designs.