IDEAS home Printed from https://ideas.repec.org/a/gam/jstats/v5y2022i1p16-269d766704.html
   My bibliography  Save this article

Resampling under Complex Sampling Designs: Roots, Development and the Way Forward

Author

Listed:
  • Pier Luigi Conti

    (Dipartimento di Scienze Statistiche, Sapienza Università di Roma, P.le Aldo Moro, 5, 00185 Roma, Italy)

  • Fulvia Mecatti

    (Dipartimento di Sociologia e Ricerca Sociale, Università di Milano-Bicocca, Via Bicocca Degli Arcimboldi, 8, 20126 Milano, Italy)

Abstract

In the present paper, resampling for finite populations under an iid sampling design is reviewed. Our attention is mainly focused on pseudo-population-based resampling due to its properties. A principled appraisal of the main theoretical foundations and results is given and discussed, together with important computational aspects. Finally, a discussion on open problems and research perspectives is provided.

Suggested Citation

  • Pier Luigi Conti & Fulvia Mecatti, 2022. "Resampling under Complex Sampling Designs: Roots, Development and the Way Forward," Stats, MDPI, vol. 5(1), pages 1-12, March.
    • Handle: RePEc:gam:jstats:v:5:y:2022:i:1:p:16-269:d:766704
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-905X/5/1/16/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2571-905X/5/1/16/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Antal, Erika & Tillé, Yves, 2011. "A Direct Bootstrap Method for Complex Sampling Designs From a Finite Population," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 534-543.
    2. Jean‐François Beaumont & Zdenek Patak, 2012. "On the Generalized Bootstrap for Sample Surveys with Special Attention to Poisson Sampling," International Statistical Review, International Statistical Institute, vol. 80(1), pages 127-148, April.
    3. Arindam Chatterjee, 2011. "Asymptotic properties of sample quantiles from a finite population," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(1), pages 157-179, February.
    4. Conti, Pier Luigi & Mecatti, Fulvia & Nicolussi, Federica, 2022. "Efficient unequal probability resampling from finite populations," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    5. Pier Luigi Conti & Daniela Marella, 2015. "Inference for Quantiles of a Finite Population: Asymptotic versus Resampling Results," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 545-561, June.
    6. Patrice Bertail & Emilie Chautru & Stephan Clémençon, 2017. "Empirical Processes in Survey Sampling with (Conditional) Poisson Designs," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 97-111, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jean-François Beaumont & Nelson Émond, 2022. "A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase," Stats, MDPI, vol. 5(2), pages 1-19, March.

    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. Daniela Marella & Paola Vicard, 2022. "Bayesian network structural learning from complex survey data: a resampling based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 981-1013, October.
    2. Wayne A. Fuller & Jason C. Legg & Yang Li, 2017. "Bootstrap Variance Estimation for Rejective Sampling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1562-1570, October.
    3. Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale, 2020. "On the estimation of the Lorenz curve under complex sampling designs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 1-24, March.
    4. Zhonglei Wang & Liuhua Peng & Jae Kwang Kim, 2022. "Bootstrap inference for the finite population mean under complex sampling designs," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1150-1174, September.
    5. Sixia Chen & David Haziza & Zeinab Mashreghi, 2022. "A Comparison of Existing Bootstrap Algorithms for Multi-Stage Sampling Designs," Stats, MDPI, vol. 5(2), pages 1-17, June.
    6. Jean-François Beaumont & Nelson Émond, 2022. "A Bootstrap Variance Estimation Method for Multistage Sampling and Two-Phase Sampling When Poisson Sampling Is Used at the Second Phase," Stats, MDPI, vol. 5(2), pages 1-19, March.
    7. Żądło Tomasz, 2021. "On the generalisation of Quatember’s bootstrap," Statistics in Transition New Series, Statistics Poland, vol. 22(1), pages 163-178, March.
    8. Marius Stefan & Michael A. Hidiroglou, 2023. "A Bootstrap Variance Procedure for the Generalised Regression Estimator," International Statistical Review, International Statistical Institute, vol. 91(2), pages 294-317, August.
    9. Pier Luigi Conti & Daniela Marella, 2015. "Inference for Quantiles of a Finite Population: Asymptotic versus Resampling Results," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 545-561, June.
    10. Tomasz Żądło, 2021. "On the generalisation of Quatember's bootstrap," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 163-178, March.
    11. Omer Ozturk & Narayanaswamy Balakrishnan & Olena Kravchuk, 2023. "Order Statistics Based on a Combined Simple Random Sample from a Finite Population and Applications to Inference," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 77-101, February.
    12. Andrius Čiginas, 2014. "On the asymptotic normality of finite population $$L$$ L -statistics," Statistical Papers, Springer, vol. 55(4), pages 1047-1058, November.
    13. M. D. Jiménez-Gamero & J. L. Moreno-Rebollo & J. A. Mayor-Gallego, 2018. "On the estimation of the characteristic function in finite populations with applications," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 95-121, March.
    14. Luca Sartore & Kelly Toppin & Linda Young & Clifford Spiegelman, 2019. "Developing Integer Calibration Weights for Census of Agriculture," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 26-48, March.
    15. Enrico Fabrizi & Caterina Giusti & Nicola Salvati & Nikos Tzavidis, 2014. "Mapping average equivalized income using robust small area methods," Papers in Regional Science, Wiley Blackwell, vol. 93(3), pages 685-701, August.
    16. Sayed A. Mostafa & Ibrahim A. Ahmad, 2021. "Kernel Density Estimation Based on the Distinct Units in Sampling with Replacement," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 507-547, November.
    17. Zhao, Puying & Haziza, David & Wu, Changbao, 2020. "Survey weighted estimating equation inference with nuisance functionals," Journal of Econometrics, Elsevier, vol. 216(2), pages 516-536.
    18. Sara Franceschi & Rosa Maria Di Biase & Agnese Marcelli & Lorenzo Fattorini, 2022. "Some Empirical Results on Nearest-Neighbour Pseudo-populations for Resampling from Spatial Populations," Stats, MDPI, vol. 5(2), pages 1-16, April.
    19. Daniela Marella, 2018. "Pc Complex: Pc Algorithm For Complex Survey Data," Departmental Working Papers of Economics - University 'Roma Tre' 0240, Department of Economics - University Roma Tre.
    20. Spencer, Neil A. & Miller, Jeffrey W., 2024. "Strong uniform laws of large numbers for bootstrap means and other randomly weighted sums," Statistics & Probability Letters, Elsevier, vol. 211(C).

    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:gam:jstats:v:5:y:2022:i:1:p:16-269:d:766704. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.