Model-Based Strategies for Oversampling Populations in Transition

• Activity Number: 295
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Health Policy Statistics Section
• Author(s): Steven Cohen*+
• Companies: AHRQ
• Keywords: medical expenditures ; oversampling ; MEPS ; model-based

Abstract

In order to satisfy analytic objectives for nationally representative population based surveys, the adopted sample designs often include oversampling techniques to ensure sufficient sample sizes are achieved for specific policy-relevant subgroups. This strategy is attractive in terms of both cost efficiency and precision, with respect to meeting underlying survey design requirements. For population subgroups defined by characteristics that are more static in nature, such as race/ethnicity, gender, age interval, and chronic conditions of long durations, ensuring sufficient sample size through the implementation of an oversampling strategy is a more straight forward operation. Alternatively, achieving sample size targets for population subgroups that are more dynamic in nature, such as the poor or near poor, individuals with high levels of medical expenditures, and the uninsured, is a more difficult enterprise. In this presentation, attention is given to the utility of a model-based approach to oversample dynamic populations, focusing on individuals likely to incur high levels of medical expenditures in a subsequent year.