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Article

Model-based estimation for population total under model misspecification using the balanced sampling scheme

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Pages 1678-1689 | Received 18 Aug 2021, Accepted 10 Mar 2022, Published online: 23 Mar 2022

References

  • Ahmed, S., and J. Shabbir. 2021. A novel basis function approach to finite population parameter estimation. Scientia Iranica. doi:10.24200/sci.2021.56353.4682.
  • Ahmed, S., J. Shabbir, S. Gupta, and F. Coolen. 2020. Estimation of small area total with randomized data. REVSTAT–Statistical Journal 18 (2):223–35.
  • Basu, D. 1971. An essay on the logical foundations of survey sampling, part I. Foundations of statistical inferences, V. P. Godambe and D. A. Sprott.
  • Belsley, D., E. Kuh, and R. Welsch. 1980. Regression diagnostics. New York: John Wiley & Sons.
  • Brewer, K. 1963. Ratio estimation and finite populations: Some results deducible from the assumption of an underlying stochastic process. Australian Journal of Statistics 5 (3):93–105. doi:10.1111/j.1467-842X.1963.tb00288.x.
  • Chambers, R. 1996. Robust case-weighting for multipurpose establishment surveys. Journal of Official Statistics 12 (1):3.
  • Chambers, R., and R. Clark. 2012. An introduction to model-based survey sampling with applications. Vol. 37. UK: Oxford University Press.
  • Chambers, R. L, and C. J. Skinner. 2003. Analysis of survey data. London: John Wiley & Sons.
  • Chauhan, S, and B. Sisodia. 2018. Model based prediction of finite population total under super population model. Journal of Reliability and Statistical Studies 11 (2):57–68.
  • Chauvet, G., D. Haziza, and É. Lesage. 2017. Examining some aspects of balanced sampling in surveys. Statistica Sinica 27 (1):313–34. doi:10.5705/ss.2013.244.
  • Cochran, W. 1940. The estimation of the yields of cereal experiments by sampling for the ratio of grain to total produce. The Journal of Agricultural Science 30 (2):262–75. doi:10.1017/S0021859600048012.
  • Cumberland, W. G, and R. Royall. 1988. Does simple random sampling provide adequate balance? Journal of the Royal Statistical Society: Series B (Methodological) 50 (1):118–24. doi:10.1111/j.2517-6161.1988.tb01717.x.
  • Deville, J.-C., and Y. Tillé. 2004. Efficient balanced sampling: The cube method. Biometrika 91 (4):893–912. doi:10.1093/biomet/91.4.893.
  • Dudoignon, L., and A. Vanheuverzwyn. 2006. Coverage optimization of the telephone surveys thanks to the inclusion of mobile phone only stratum. Mediametrie Papers.
  • Falorsi, P. D, and P. Righi. 2016. A unified approach for defining optimal multivariate and multi-domains sampling designs. In Topics in theoretical and applied statistics, 145–52. Switzerland: Springer.
  • Godambe, V. 1955. A unified theory of sampling from finite populations. Journal of the Royal Statistical Society: Series B (Methodological) 17 (2):269–78.
  • Hazlett, C. 2013. A balancing method to equalize multivariate densities and reduce bias without a specification search. Working draft.
  • Jafaraghaie, R. 2022. Prediction of finite population parameters using parametric model under some loss functions. Communications in Statistics-Theory and Methods 51 (4):863–82.
  • Kawakubo, Y., and G. Kobayashi. 2019. Small area estimation of general finite-population parameters based on grouped data. arXiv Preprint arXiv:1903.07239.
  • Kikechi, C. B. 2020. On local polynomial regression estimators in finite population. International Journal of Statistics and Applied Mathematics 5 (1):58–63.
  • Kikech, C. B., R. O. Simwa, and G. P. Pokhariyal. 2019. On prediction based robust estimators of finite population totals. International Journal of Statistics and Applied Mathematics 4 (6):101–7.
  • Molina, I, and M. Ghosh. 2021. Accounting for dependent informative sampling in model-based finite population inference. TEST 30 (1):179–97. doi:10.1007/s11749-020-00708-0.
  • Périé, P. 2008. Échantillonnage à entropie maximale sous contraintes: Un algorithme rapide basé sur l’optimisation linéaire en nombres binaires. Méthodes D’enquêtes: Applications Aux Enquêtes Longitudinales, à la Santé et Aux Enquêtes Électorales: 294–9.
  • Royall, R. 1992. Robustness and optimal design under prediction models for finite populations. Survey Methodology 18 (2):179–85.
  • Royall, R. M. 1970. On finite population sampling theory under certain linear regression models. Biometrika 57 (2):377–87. doi:10.1093/biomet/57.2.377.
  • Royall, R. M. 1976a. Likelihood functions in finite population sampling theory. Biometrika 63 (3):605–14. doi:10.1093/biomet/63.3.605.
  • Royall, R. M. 1976b. The linear least-squares prediction approach to two-stage sampling. Journal of the American Statistical Association 71 (355):657–64. doi:10.1080/01621459.1976.10481542.
  • Royall, R. M., and W. G. Cumberland. 1981. The finite-population linear regression estimator and estimators of its variance—An empirical study. Journal of the American Statistical Association 76 (376):924–30.
  • Royall, R. M., and J. Herson. 1973. Robust estimation in finite populations I. Journal of the American Statistical Association 68 (344):880–9. doi:10.1080/01621459.1973.10481440.
  • Royall, R. M, and D. Pfeffermann. 1982. Balanced samples and robust Bayesian inference in finite population sampling. Biometrika 69 (2):401–9. doi:10.1093/biomet/69.2.401.
  • Scott, A., K. Brewer, and E. Ho. 1978. Finite population sampling and robust estimation. Journal of the American Statistical Association 73 (362):359–61. doi:10.1080/01621459.1978.10481582.
  • Valliant, R. A. H. Dorfman, and R. M. Royall. 2000. Finite population sampling and inference: A prediction approach. Number 04; QA276. 6, V3. New York: John Wiley.

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