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Analysis of Ordinal Populations from Judgment Post-Stratification

Author

Listed:
  • Amirhossein Alvandi

    (Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA 01003, USA)

  • Armin Hatefi

    (Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John’s, NL A1C 5S7, Canada)

Abstract

In surveys requiring cost efficiency, such as medical research, measuring the variable of interest (e.g., disease status) is expensive and/or time-consuming; however, we often have access to easily obtainable characteristics about sampling units. These characteristics are not typically employed in the data collection process. Judgment post-stratification (JPS) sampling enables us to supplement the random samples from the population of interest with these characteristics as ranking information. This paper develops methods based on the JPS samples for estimating categorical ordinal populations. We develop various estimators from the JPS data even for situations where the JPS suffers from empty strata. We also propose the JPS estimators using multiple ranking resources. Through extensive numerical studies, we evaluate the performance of the methods in estimating the population. Finally, the developed estimation methods are applied to bone mineral data to estimate the bone disorder status of women aged 50 and older.

Suggested Citation

  • Amirhossein Alvandi & Armin Hatefi, 2023. "Analysis of Ordinal Populations from Judgment Post-Stratification," Stats, MDPI, vol. 6(3), pages 1-27, August.
    • Handle: RePEc:gam:jstats:v:6:y:2023:i:3:p:52-838:d:1213504
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    References listed on IDEAS

    as
    1. Xinlei Wang & Johan Lim & Lynne Stokes, 2008. "A Nonparametric Mean Estimator for Judgment Poststratified Data," Biometrics, The International Biometric Society, vol. 64(2), pages 355-363, June.
    2. Ozturk, Omer, 2014. "Statistical inference for population quantiles and variance in judgment post-stratified samples," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 188-205.
    3. Ali Dastbaravarde & Nasser Reza Arghami & Majid Sarmad, 2016. "Some theoretical results concerning non parametric estimation by using a judgment poststratification sample," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(8), pages 2181-2203, April.
    4. Frey, Jesse & Feeman, Timothy G., 2012. "An improved mean estimator for judgment post-stratification," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 418-426.
    5. Zamanzade, Ehsan & Wang, Xinlei, 2017. "Estimation of population proportion for judgment post-stratification," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 257-269.
    6. Xinlei Wang & Ke Wang & Johan Lim, 2012. "Isotonized CDF Estimation from Judgment Poststratification Data with Empty Strata," Biometrics, The International Biometric Society, vol. 68(1), pages 194-202, March.
    7. Wang, Xinlei & Stokes, Lynne & Lim, Johan & Chen, Min, 2006. "Concomitants of Multivariate Order Statistics With Application to Judgment Poststratification," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1693-1704, December.
    8. Armin Hatefi & Amirhossein Alvandi, 2022. "Efficient estimators with categorical ranked set samples: estimation procedures for osteoporosis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(4), pages 803-818, March.
    Full references (including those not matched with items on IDEAS)

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