Using a model-aided sampling paradigm instead of a traditional sampling paradigm in a nationally representative establishment survey
We compare traditional survey inference, which is based on probability sample selection and weighting, with a model-based approach based on sampling quotas and model-based weighting. Compared with the traditional approach, the model-based approach more efficiently controls subgroup sample sizes when a large number of rare subgroups are studied. Using data from a national survey of US businesses, we simulated a model-based paradigm and compared estimates with those under the traditional paradigm. In this study, the findings suggest that the model-based approach offers advantages over the traditional sampling approach; however, a hybrid approach capturing the advantages of both paradigms proved best.
Berzofsky, M., Welch, B., Williams, R., & Biemer, P. (2008). Using a model-aided sampling paradigm instead of a traditional sampling paradigm in a nationally representative establishment survey. (RTI Press Publication No. MR-0004-0802). Research Triangle Park, NC: RTI Press. DOI: 10.3768/rtipress.2008.mr.0004.0802