The U.S. Census Bureau hosted a webinar today, May 27, at 2:00 p.m. ET, to demonstrate how cross-survey modeling enhances the usefulness of federal data products. This innovative approach utilizes machine learning to bridge data gaps between various surveys.
The webinar, led by speaker Chase Sawyer, detailed the methodology behind this technique. Participants learned how cross-survey modeling was specifically applied to integrate a variable from the American Housing Survey into the American Community Survey, thereby enriching the overall data landscape.
This method aims to improve the utility and coherence of federal data, offering more comprehensive insights for a wide range of applications.