Record Linkage in Statistical Sampling: Past, Present, and Future

Author:

Williams Benjamin

Publisher

Springer International Publishing

Reference52 articles.

1. Abowd, J. M., Abramowitz, J., Levenstein, M. C., Mccue, K., Patki, D., Raghunathan, T., Rodgers, A. M., Shapiro, M. D., & Wasi, N. (2019). Optimal probabilistic record linkage: Best practice for linking employers in survey and administrative data. Center for Economic Studies Working Paper Series Working Paper Number CES-19-08.

2. Amaya, A., Biemer, P. P., & Kinyon, D. (2020). Total error in a big data world: Adapting the TSE framework to big data. Journal of Survey Statistics and Methodology, 8(1), 89–119. https://doi.org/10.1093/jssam/smz056

3. Baker, R., J. M. Brick, Bates, N. A., Battaglia, M., Couper, M. P., Dever, J. A., Gile, K. J., & Tourangeau, R. (2013). Report of the AAPOR task force on non-probability sampling. American Association for Public Opinion Research. www.aapor.org/AAPOR_Main/media/MainSiteFiles/NPS_TF_Report_Final_7_revised_FNL_6_22_13.pdf

4. Bell, R. M. (2017). Diverse applications of probabilistic record linkage: Schucany lecture series. Southern Methodist University.

5. Bell, R. M., Keesey, J., & Richards, T. (1994). The urge to merge: Linking vital statistics records and Medicaid claims. In Medical care (pp. 1004–1018).

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