The great weight debate: Constructing, exploring, and visualizing survey weights to enhance representativeness and obtain population-level estimates from NCHA-II data
College and university administrations across the US utilize results from the National College Health Assessment (NCHA) surveys conducted on their campuses to make decisions about student health policy. When the NCHA is administered through voluntary response sampling, how representative are the responses that administrations get? This project focuses on weighting responses from the NCHA-II survey conducted at a small liberal arts college to improve its representativeness and promote data-driven policy making. The aims of the project are (1) identifying and selecting weighting variables by comparing sample and population demographics and (2) comparing and analyzing raking and post-stratification weighting methods to select a reasonable weighting technique for this data. Innovative visualizations provide key insights into both components of the project. We found that, consistent with previous literature, raking generated more reliable weights for this situation. We also suggest ways to incorporate constructed weights into future analysis.