[Blackwell, D., and J.B. MacQueen. 1973. “Ferguson Distributions via Polya Urn Schemes.” The Annals of Statistics, 1:353–355. DOI: http://dx.doi.org/10.1214/aos/1176342372.10.1214/aos/1176342372]Search in Google Scholar
[CDC. 2015. National Health and Nutrition Examination Survey Data. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. Available at: http://www.cdc.gov/nchs/nhanes.htm (accessed January 2015).]Search in Google Scholar
[Chen, Q., M.R. Elliott, and R.J.A. Little. 2010. “Bayesian Penalized Spline Model-Based Inference for Finite Population Proportions in Unequal Probability Sampling.” Survey Methodology, 36:22–34.]Search in Google Scholar
[Chen, Q., M.R. Elliott, and R.J.A. Little 2012. “Bayesian Inference for Finite Population Quantiles from Unequal Probability Samples.” Survey Methodology, 38:203–215.]Search in Google Scholar
[Chen, Q., X. Jiang, E. Hedgeman, K. Knutson, B. Gillespie, B. Hong, J.M. Lepkowski, A. Franzblau, O. Jolliet, P. Adriaens, A.H. Demond, and D.H. Garabrant. 2013. “Estimation of age- and sex-specific background human serum concentrations of PCDDs, PCDFs, and PCBs in the UMDES and NHANES populations.” Chemosphere, 91:817–823. DOI: http://dx.doi.org/10.1016/j.chemosphere.2013.01.078.10.1016/j.chemosphere.2013.01.07823466097]Search in Google Scholar
[Dunson, D.R., N. Pillai, and J.-H. Park. 2007. “Bayesian density regression.” Journal of the Royal Statistical Society, B69:163–183. DOI: http://dx.doi.org/10.1111/j.1467-9868.2007.00582.x.10.1111/j.1467-9868.2007.00582.x]Search in Google Scholar
[Elliott, M.R. 2007. “Bayesian weight trimming for generalized linear regression models.” Survey Methodology, 33:23–24.]Search in Google Scholar
[Ericson, W.A. 1969. “Subjective Bayesian modeling in sampling finite populations.” Journal of the Royal Statistical Society, 31:195–234. DOI: https://doi.org/10.1111/j.2517-6161.1969.tb00782.x.10.1111/j.2517-6161.1969.tb00782.x]Search in Google Scholar
[Ferguson, T. 1973. “A Bayesian Analysis of Some Nonparametric Problems.” Annals of Statistics, 1:209–230. DOI: http://dx.doi.org/10.1214/aos/1176342360.10.1214/aos/1176342360]Search in Google Scholar
[Fienberg, S.E. 2011. “Bayesian Models and Methods in Public Policy and Government Settings.” Statistical Science, 26:212–226. DOI: http://dx.doi.org/10.1214/10-STS331.10.1214/10-STS331]Search in Google Scholar
[Hoffman, A., and A. Gelman. 2014. “The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo.” Journal of Machine Learning Research, 15:1593–1623.]Search in Google Scholar
[Holt, D., and T.M.F. Smith. 1979. “Post Stratification.” Journal of the Royal Statistical Society, 142:33–46. DOI: https://doi.org/10.2307/2344652.10.2307/2344652]Search in Google Scholar
[Little, R.J.A. 1993. “Post Stratification: A Modeler’s Perspective.” Journal of the American Statistical Association, 88:1001–1012. DOI: http://dx.doi.org/10.1080/01621459.1993.10476368.10.1080/01621459.1993.10476368]Search in Google Scholar
[Little, R.J.A. 2012. Calibrated Bayes, An Alternative Inferential Paradigm for Official Statistics.” Journal of Official Statistics, 28:309–334. Available at: https://www.scb.se/contentassets/ca21efb41fee47d293bbee5bf7be7fb3/calibrated-bayes-an-alternative-inferential-paradigm-for-official-statistics.pdf (accessed January 2021).]Search in Google Scholar
[Lu, H., and A. Gelman. 2003. “A Method for Estimating Design-Based Sampling Variances For Surveys with Weighting, Poststratification, and Raking.” Journal of Official Statistics, 19:133–151. Available at: https://www.scb.se/contentassets/-ca21efb41fee47d293bbee5bf7be7fb3/a-method-for-estimating-design-based-sampling-variances-for-surveys-with-weighting-poststratification-and-raking.pdf (accessed January 2021).]Search in Google Scholar
[MacEachern, S.N. 1994. “Estimating normal means with a conjugate style Dirichlet process prior.” Communications in Statistics – Simulation and Computation, 23:727–741. DOI: http://dx.doi.org/10.1080/03610919408813196.10.1080/03610919408813196]Search in Google Scholar
[Murty, K.G. 1983. Linear programming. New York: Wiley.]Search in Google Scholar
[Potter, F. 1990. “A study of procedures to identify and trim extreme sample weights.” Proceedings of the Section on Survey Research Methods, American Statistical Association: 225–230.]Search in Google Scholar
[Rubin, D.B. 1983. Comment on “An Evaluation of Model-Dependent and Probability Sampling Inferences in Sampling Surveys” by M.H. Hansen, W.G. Madow, and B.J. Tepping. Journal of the American Statistical Association, 78:803–805.10.2307/2288187]Search in Google Scholar
[Rubin, D.B. 1987. Multiple Imputation for Non-Response in Surveys. Wiley: New York.10.1002/9780470316696]Search in Google Scholar
[Si, Y., N. Pillai, and A. Gelman. 2015. “Bayesian Nonparametric Weighted Sampling Inference.” Bayesian Analysis, 10:605–625. DOI: http://dx.doi.org/10.1214/14-BA924.10.1214/14-BA924]Search in Google Scholar
[Skinner, C.J., D. Holt, and T.M.F. Smith. 1989. Analysis of Complex Surveys. Wiley: New York.]Search in Google Scholar
[Wang, Y. 1998. “Smoothing Spline Models with Correlated Random Errors.” Journal of the American Statistical Association, 93:341–348. DOI: http://dx.doi.org/10.1080/01621459.1998.10474115.10.1080/01621459.1998.10474115]Search in Google Scholar
[Yu, K., and R.A. Moyeed. 2001. “Bayesian quantile regression.” Statistics and Probability Letters, 54:437–447. DOI: https://doi.org/10.1016/S0167-7152(01)00124-9.10.1016/S0167-7152(01)00124-9]Search in Google Scholar
[Zangeneh, S.Z., and R.J.A. Little. 2015. “Bayesian Inference for the Finite Population Total from a Heteroscedastic Probability Proportional to Size Sample.” Journal of Survey Statistics and Methodology, 3:162–192. DOI: http://dx.doi.org/10.1093/jssam/smv002.10.1093/jssam/smv002]Search in Google Scholar
[Zheng, H., and R.J.A. Little. 2003. “Penalized Spline Model-Based Estimation of the Finite Populations Total from Probability-Proportional-to-Size Samples.” Journal of Official Statistics, 19:99 – 117. Available at: https://www.scb.se/contentassets/-ca21efb41fee47d293bbee5bf7be7fb3/penalized-spline-model-based-estimation-of-thefinite-populations-total-from-probability-proportional-to-size-samples.pdf (accessed January 2021).]Search in Google Scholar