More efficient identification of households with children can help researchers reduce survey screening costs while maintaining statistical efficiency.
In a newly published article, Westat researchers examine how variables appended by address-based sampling (ABS) frame vendors can improve the process of identifying households with children ages 5–17. The study demonstrates that using a combination of ABS-appended variables in a stratified sample design can more efficiently identify eligible households and reduce screening costs. The research also highlights the importance of monitoring the quality of appended data and using effective sample size to assess the statistical efficiency of stratified sampling.
“Child-focused surveys face a fundamental challenge: Most U.S. households do not have children, yet identifying the households that do requires substantial screening,” explains Daifeng Han, PhD, a Westat Associate Vice President for Statistics and Data Science. “Our research shows that thoughtfully combining information available on the sampling frame can help identify those households more efficiently—potentially reducing screening costs while maintaining the level of statistical precision needed for high-quality estimates.”
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Daifeng Han and Sipeng Wang