Combining multiple imperfect data sources for small area estimation: a Bayesian model of provincial fertility rates in Cambodia

References

• Asian Development Bank. (2014). Cambodia country poverty analysis 2014. Manila: Asian Development Bank.
   Google Scholar
• Bijak, J., & Bryant, J. (2016). Bayesian demography 250 years after Bayes. Population Studies, 70(1), 1–19. doi: 10.1080/00324728.2015.1122826
   PubMed Web of Science ®Google Scholar
• Brick, J. M., Cervantes, I. F., Lee, S., & Norman, G. (2011). Nonsampling errors in dual frame telephone surveys. Survey Methodology, 37, 1–12.
   Web of Science ®Google Scholar
• Bryant, J., & Zhang, J. L. (2018). Bayesian demographic estimation and forecasting. Boca Raton: CRC Press.
   Google Scholar
• Christen, P. (2012). Data matching: Concepts and techniques for record linkage, entity resolution, and duplicate detection. New York, NY: Springer Science and Business Media.
   Google Scholar
• Dwyer-Lindgren, L., Squires, E. R., Teeple, S., Ikilezi, G., Roberts, D. A., Colombara, D. V., …Lim, S. S. (2018). Small area estimation of under-5 mortality in Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia using spatially misaligned data. Population Health Metrics, 16(13), 1–15.
   Google Scholar
• Fay, R. E. I., & Herriot, R. A. (1979). Estimates of income for small places: An application of James–Stein procedures to census data. Journal of the American Statistical Association, 74, 269–277. doi: 10.1080/01621459.1979.10482505
   Web of Science ®Google Scholar
• Gelman, A., Carlin, J., Stern, H., Dunson, D. B., Vehtari, A., & Rubin, D. (2014). Bayesian data analysis (3rd ed.). New York, NY: Chapman and Hall.
   Google Scholar
• Gelman, A., King, G., & Liu, C. (1998). Not asked and not answered: Multiple imputation for multiple surveys. Journal of the American Statistical Association, 93, 846–857. doi: 10.1080/01621459.1998.10473737
   Web of Science ®Google Scholar
• Harron, K., Goldstein, H., & Dibben, C. (2016). Methodological developments in data linkage. Hoboken, NJ: Wiley.
   Google Scholar
• He, Y., Landrum, M. B., & Zaslavsky, A. M. (2014). Combining information from two data sources with misreporting and incompleteness to assess hospice-use among cancer patients: A multiple imputation approach. Statistics in Medicine, 33, 3710–3724. doi: 10.1002/sim.6173
   Web of Science ®Google Scholar
• Herzog, T. N., Scheuren, F. J., & Winkler, W. E. (2017). Data quality and record linkage techniques. New York, NY: Springer Science and Business Media.
   Google Scholar
• Kim, J. K., Park, S., & Kim, S. Y. (2015). Small area estimation combining information from several sources. Survey Methodology, 41(1), 21–36.
   Web of Science ®Google Scholar
• Kim, J. K., & Rao, J. N. K. (2012). Combining data from two independent surveys: A model-assisted approach. Biometrika, 99, 85–100. doi: 10.1093/biomet/asr063
   Web of Science ®Google Scholar
• Knutson, K., Zhang, W., & Tabnak, F. (2008). Applying the small-area estimation method to estimate a population eligible for breast cancer detection. Preventing Chronic Disease, 5(1), A10.
   Google Scholar
• Lesser, V. M., Newton, L., & Yang, D (2008). Evaluating frames and modes of contact in a study of individuals with disabilities. Paper presented at the Joint Statistical Meetings, Denver, CO.
   Google Scholar
• Lohr, S. L., & Raghunathan, T. E. (2017). Combining survey data with other data sources. Statistical Science, 32(2), 293–312. doi: 10.1214/16-STS584
   Web of Science ®Google Scholar
• Lohr, S. L., & Rao, J. N. K. (2006). Estimation in multiple-frame surveys. Journal of the American Statistical Association, 101, 1019–1030. doi: 10.1198/016214506000000195
   Web of Science ®Google Scholar
• Lumley, T. (2004). Analysis of complex survey samples. Journal of Statistical Software, 9(1), 1–19.
   Google Scholar
• Lynch, S. M., & Brown, J. S. (2010). Obtaining multistate life table distributions for highly refined subpopulations from cross-sectional data: A Bayesian extension of Sullivan's method. Demography, 47(4), 1053–1077. doi: 10.1007/BF03213739
   PubMed Web of Science ®Google Scholar
• Manzi, G., Spiegelhalter, D. J., Turner, R. M., Flowers, J., & Thompson, S. G. (2011). Modelling bias in combining small area prevalence estimates from multiple surveys. Journal of the Royal Statistical Society: Series A, 174(1), 31–50. doi: 10.1111/j.1467-985X.2010.00648.x
   Google Scholar
• Metcalf, P., & Scott, A. (2009). Using multiple frames in health surveys. Statistics in Medicine, 28, 1512–1523. doi: 10.1002/sim.3566
   PubMed Web of Science ®Google Scholar
• Moultrie, T. A., Dorrington, R., Hill, A., Hill, K., Timæus, I., & Zaba, B. (2013). Tools for demographic estimation. Paris: International Union for the Scientific Study of Population.
   Google Scholar
• National Institute of Statistics, Directorate General for Health, & ICF Macro. (2011a). Cambodia demographic and health survey 2010. Author.
   Google Scholar
• National Institute of Statistics, Directorate General for Health, & ICF Macro (2011b). Cambodia demographic and health survey 2010 [Dataset] (khir61fl.dta). Author.
   Google Scholar
• Pfeffermann, D. (2013). New important developments in small area estimation. Statistical Science, 28(1), 40–68. doi: 10.1214/12-STS395
   Web of Science ®Google Scholar
• Prado, R., & West, M. (2010). Time series: Modeling, computation, and inference. Boca Raton, FL: CRC Press.
   Google Scholar
• Preston, S., Heuveline, P., & Guillot, M. (2001). Demography: Modelling and measuring population processes. Oxford: Blackwell.
   Google Scholar
• Raghunathan, T. E. (2006). Combining information from multiple surveys for assessing health disparities. Allgemeines Statistisches Archiv, 90, 515–526. doi: 10.1007/s10182-006-0003-0
   Google Scholar
• Raghunathan, T., Xie, D., Schenker, N., Parsons, V., Davis, W., Dodd, K., & Feuer, E. (2007). Combining information from two surveys to estimate county-level prevalence rates of cancer risk factors and screening. Journal of the American Statistical Association, 102, 474–486. doi: 10.1198/016214506000001293
   Web of Science ®Google Scholar
• Ranalli, M. G., Arcos, A., Rueda, M. D. M., & Teodoro, A. (2016). Calibration estimation in dual-frame surveys. Statistical Methods and Applications, 25, 321–349. doi: 10.1007/s10260-015-0336-5
   Web of Science ®Google Scholar
• Rao, J. N. K., & Molina, I. (2015). Small area estimation (2nd ed.). Hoboken: John Wiley & Sons.
   Google Scholar
• Schenker, N., Raghunathan, T. E., & Bondarenko, I. (2010). Improving on analyses of self-reported data in a large-scale health survey by using information from an examination-based survey. Statistics in Medicine, 29, 533–545.
   PubMed Web of Science ®Google Scholar
• Schmertmann, C. P., Cavenaghi, S. M., Assunção, R. M., & Potter, J. E. (2013). Bayes plus Brass: Estimating total fertility for many small areas from sparse census data. Population Studies, 67(3), 255–273. doi: 10.1080/00324728.2013.795602
   PubMed Web of Science ®Google Scholar
• Steorts, R. C., Hall, R., & Fienberg, S. E. (2016). A Bayesian approach to graphical record linkage and de-duplication. Journal of the American Statistical Association, 111, 1660–1672. doi: 10.1080/01621459.2015.1105807
   Web of Science ®Google Scholar
• Zhang, J. L., Bryant, J., & Nissen, K. (2019). Bayesian small area demography. Survey Methodology, 45(1), 13–29.
   Web of Science ®Google Scholar