IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0324559.html
   My bibliography  Save this article

Estimation of finite population mean in a complex survey sampling

Author

Listed:
  • Mohsin Abbas
  • Muhammad Ahmed Shehzad
  • Mahwish Rabia
  • Haris Khurram
  • Muhammad Ijaz

Abstract

Accurate estimation of the finite population mean is a fundamental challenge in survey sampling, especially when dealing with large or complex populations. Traditional methods like simple random sampling may not always provide reliable or efficient estimates in such cases. Motivated by this, the current study explores complex sampling techniques to improve the precision and accuracy of mean estimators. Specifically, we employ two-stage and three-stage cluster sampling methods to develop unbiased estimators for the finite population mean. Building upon these, the next phase of the study formulates unbiased mean estimators using stratified two- and three-stage cluster sampling. To further enhance the precision of these estimators, a ranked-set sampling strategy is applied to the secondary and tertiary sampling stages. Additionally, unbiased variance estimators corresponding to the proposed mean estimators are derived. Real-world datasets are utilized to demonstrate the application of these complex survey sampling methodologies, with results showing that the mean estimates derived using ranked set sampling are more accurate than those obtained via simple random sampling.

Suggested Citation

  • Mohsin Abbas & Muhammad Ahmed Shehzad & Mahwish Rabia & Haris Khurram & Muhammad Ijaz, 2025. "Estimation of finite population mean in a complex survey sampling," PLOS ONE, Public Library of Science, vol. 20(5), pages 1-24, May.
  • Handle: RePEc:plo:pone00:0324559
    DOI: 10.1371/journal.pone.0324559
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0324559
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0324559&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0324559?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Al-Omari, Amer Ibrahim, 2012. "Ratio estimation of the population mean using auxiliary information in simple random sampling and median ranked set sampling," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 1883-1890.
    2. Shashi Bhushan & Anoop Kumar & Sana Shahab & Showkat Ahmad Lone & Salemah A. Almutlak, 2022. "Modified Class of Estimators Using Ranked Set Sampling," Mathematics, MDPI, vol. 10(21), pages 1-13, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Usman Shahzad & Ishfaq Ahmad & Ibrahim Mufrah Almanjahie & Amer Ibrahim Al-Omari, 2022. "Three-fold utilization of supplementary information for mean estimation under median ranked set sampling scheme," PLOS ONE, Public Library of Science, vol. 17(10), pages 1-26, October.
    2. Sweta Shukla & Abhishek Singh & Gajendra K. Vishwakarma, 2025. "Predictive estimation for mean under median ranked set sampling: an application to COVID-19 data," Indian Journal of Pure and Applied Mathematics, Springer, vol. 56(1), pages 218-229, March.
    3. Hani Samawi & Lili Yu & JingJing Yin, 2023. "On Cox proportional hazards model performance under different sampling schemes," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-15, April.
    4. Neeraj Tiwari & Girish Chandra & Shailja Bhari & Jharna Banerjie, 2025. "Estimation of Location and Scale Parameters of Lognormal Distribution Using Median with Extreme Ranked Set Sampling," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 87(1), pages 76-102, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0324559. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.