IDEAS home Printed from https://ideas.repec.org/a/spr/metron/v76y2018i2d10.1007_s40300-017-0131-1.html
   My bibliography  Save this article

Dealing sensitive characters on successive occasions through a general class of estimators using scrambled response techniques

Author

Listed:
  • Kumari Priyanka

    (University of Delhi)

  • Pidugu Trisandhya

    (University of Delhi)

  • Richa Mittal

    (NIT Calicut)

Abstract

Present article endeavours to propose a general class of estimators to estimate population mean of a sensitive character using non-sensitive auxiliary information under five different scrambled response models in two occasions successive sampling. Various well-known estimators have been modified for the estimation of sensitive population mean and hence they also become a member of proposed general class of estimators. Properties of proposed class of estimators have been derived and checked empirically while comparing the proposed class of estimators with respect to modified Jessen (Iowa Agric Exp Stn Res Bull 304:1–104, 1942) type estimator and modified Singh (Stat Transit 7(1):21–26, 2005) type estimator under five different scrambled response models. The effectiveness of different models has been discussed while comparing it with the direct questioning methods. A model for optimum total cost has also been proposed. Privacy protection has been elaborated for all considered models. Numerical illustrations including simulation studies are abundant to the theoretical results. Finally suitable recommendations are forwarded.

Suggested Citation

  • Kumari Priyanka & Pidugu Trisandhya & Richa Mittal, 2018. "Dealing sensitive characters on successive occasions through a general class of estimators using scrambled response techniques," METRON, Springer;Sapienza Università di Roma, vol. 76(2), pages 203-230, August.
    • Handle: RePEc:spr:metron:v:76:y:2018:i:2:d:10.1007_s40300-017-0131-1
    DOI: 10.1007/s40300-017-0131-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40300-017-0131-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40300-017-0131-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zawar Hussain & Bander Al-Zahrani, 2016. "Mean and sensitivity estimation of a sensitive variable through additive scrambling," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(1), pages 182-193, January.
    2. Giancarlo Diana & Pier Perri, 2011. "A class of estimators for quantitative sensitive data," Statistical Papers, Springer, vol. 52(3), pages 633-650, August.
    3. Sat Gupta & Javid Shabbir, 2008. "On improvement in estimating the population mean in simple random sampling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(5), pages 559-566.
    4. Sarjinder Singh & Stephen A. Sedory, 2012. "A true simulation study of three estimators at equal protection of respondents in randomized response sampling," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(4), pages 442-451, November.
    5. Giancarlo Diana & Pier Francesco Perri, 2010. "New scrambled response models for estimating the mean of a sensitive quantitative character," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1875-1890.
    6. Amitava Saha, 2007. "A simple randomized response technique in complex surveys," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 59-66.
    7. Housila P. Singh & Gajendra K. Vishwakarma, 2007. "A general class of estimators in successive sampling," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 201-227.
    8. Jong-Min Kim & Matthew Elam, 2007. "A stratified unrelated question randomized response model," Statistical Papers, Springer, vol. 48(2), pages 215-233, April.
    9. Richa Mittal & Kumari Priyanka, 2014. "Effective Rotation Patterns for Median Estimation in Successive Sampling," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(2), pages 197-220, March.
    10. Jun-Wu Yu & Guo-Liang Tian & Man-Lai Tang, 2008. "Two new models for survey sampling with sensitive characteristic: design and analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(3), pages 251-263, April.
    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. Kumari Priyanka & Pidugu Trisandhya, 2019. "Modelling Sensitive Issues On Successive Waves," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 41-65, March.
    2. Lucio Barabesi & Giancarlo Diana & Pier Perri, 2013. "Design-based distribution function estimation for stigmatized populations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(7), pages 919-935, October.
    3. Priyanka Kumari & Trisandhya Pidugu, 2019. "Modelling Sensitive Issues On Successive Waves," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 41-65, March.
    4. Horng-Jinh Chang & Mei-Pei Kuo, 2012. "Estimation of population proportion in randomized response sampling using weighted confidence interval construction," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(5), pages 655-672, July.
    5. María del Mar García Rueda & Pier Francesco Perri & Beatriz Rodríguez Cobo, 2018. "Advances in estimation by the item sum technique using auxiliary information in complex surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(3), pages 455-478, July.
    6. Lucio Barabesi & Giancarlo Diana & Pier Perri, 2015. "Gini index estimation in randomized response surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 45-62, January.
    7. Antonio Arcos & María del Rueda & Sarjinder Singh, 2015. "A generalized approach to randomised response for quantitative variables," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 1239-1256, May.
    8. María del Mar Rueda & Beatriz Cobo & Antonio Arcos, 2021. "Regression Models in Complex Survey Sampling for Sensitive Quantitative Variables," Mathematics, MDPI, vol. 9(6), pages 1-13, March.
    9. Mausumi Bose, 2015. "Respondent privacy and estimation efficiency in randomized response surveys for discrete-valued sensitive variables," Statistical Papers, Springer, vol. 56(4), pages 1055-1069, November.
    10. Carlos Barros, 2012. "Sustainable Tourism in Inhambane-Mozambique," CEsA Working Papers 105, CEsA - Centre for African and Development Studies.
    11. Andreas Lagerås & Mathias Lindholm, 2020. "How to ask sensitive multiple‐choice questions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 397-424, June.
    12. Sardar Hussain & Sohaib Ahmad & Mariyam Saleem & Sohail Akhtar, 2020. "Finite population distribution function estimation with dual use of auxiliary information under simple and stratified random sampling," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-30, September.
    13. Burgstaller, Lilith & Feld, Lars P. & Pfeil, Katharina, 2022. "Working in the shadow: Survey techniques for measuring and explaining undeclared work," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 661-671.
    14. Kazuo Yamaguchi, 2016. "Cross-sectional and Panel Data Analyses of an Incompletely Observed Variable Derived From the Nonrandomized Method for Surveying Sensitive Questions," Sociological Methods & Research, , vol. 45(1), pages 41-68, February.
    15. Pavel Dietz & Anne Quermann & Mireille Nicoline Maria van Poppel & Heiko Striegel & Hannes Schröter & Rolf Ulrich & Perikles Simon, 2018. "Physical and cognitive doping in university students using the unrelated question model (UQM): Assessing the influence of the probability of receiving the sensitive question on prevalence estimation," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-12, May.
    16. Surya K. Pal & Housila P. Singh, 2017. "Estimation of finite population mean using auxiliary information in systematic sampling," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1392-1398, November.
    17. Ndlovu N & Mafumbate J & Mafuka A & Brena M, 2017. "The Impact of the Buy Zimbabwe Campaign on Performance of Zimbabwean Companies in the Retail Sector," Journal of Economics and Behavioral Studies, AMH International, vol. 8(6), pages 227-236.
    18. Pier Francesco Perri & Eleni Manoli & Tasos C. Christofides, 2023. "Assessing the effectiveness of indirect questioning techniques by detecting liars," Statistical Papers, Springer, vol. 64(5), pages 1483-1506, October.
    19. Zoramthanga Ralte & Gitasree Das, 2015. "Ratio-To-Regression Estimator In Successive Sampling Using One Auxiliary Variable," Statistics in Transition New Series, Polish Statistical Association, vol. 16(2), pages 183-202, June.
    20. Marc Höglinger & Ben Jann, 2018. "More is not always better: An experimental individual-level validation of the randomized response technique and the crosswise model," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-22, August.

    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:spr:metron:v:76:y:2018:i:2:d:10.1007_s40300-017-0131-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.