Weighting Nonprobability and Probability Sample Surveys in Describing Cancer Catchment Areas

Abstract Background: The Population Health Assessment initiative by NCI sought to enhance cancer centers’ capacity to acquire, aggregate, and integrate data from multiple sources, as well as to plan, coordinate, and enhance catchment area analysis activities. Methods: Key objectives of this initiative are pooling data and comparing local data with national data. A novel aspect of analyzing data from this initiative is the methodology used to weight datasets from sites that collected both probability and nonprobability samples. This article describes the methods developed to weight data, which cancer centers collected with combinations of probability, and nonprobability sampling designs. Results: We compare alternative weighting methods in particular for the hybrid probability and nonprobability sampling designs employed by different cancer centers. We also include comparisons of local center data with national survey data from large probability samples. Conclusions: This hybrid approach to calculating statistical weights can be implemented both within cancer centers that collect both probability and nonprobability samples with common measures. Aggregation can also apply to cancer centers that share common data elements, and target similar populations, but differ in survey sampling designs. Impact: Researchers interested in local versus national comparisons for cancer surveillance and control outcomes should consider various weighting approaches, including hybrid approaches, when analyzing their data.