IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v80y2010i23-24p1947-1953.html
   My bibliography  Save this article

An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies

Author

Listed:
  • Bhattacharya, Rabi
  • Lin, Lizhen

Abstract

We present a novel nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages. The asymptotic theory for the methodology is derived, showing that the MISEs (mean integrated squared error) of the estimates of both the dose-response curve F and its inverse F-1 achieve the optimal rate O(N-4/5). Also, we compute the asymptotic distribution of the estimate of the effective dosage [zeta]p=F-1(p) which is shown to have an optimally small asymptotic variance.

Suggested Citation

  • Bhattacharya, Rabi & Lin, Lizhen, 2010. "An adaptive nonparametric method in benchmark analysis for bioassay and environmental studies," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1947-1953, December.
  • Handle: RePEc:eee:stapro:v:80:y:2010:i:23-24:p:1947-1953
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(10)00247-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Dette, Holger & Neumeyer, Natalie & Pilz, Kay F., 2005. "A Note on Nonparametric Estimation of the Effective Dose in Quantal Bioassay," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 503-510, June.
    2. G. W. Cran, 1980. "Amalgamation of Means in the Case of Simple Ordering," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 209-211, June.
    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. Walter W. Piegorsch & Hui Xiong & Rabi N. Bhattacharya & Lizhen Lin, 2014. "Benchmark Dose Analysis via Nonparametric Regression Modeling," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 135-151, January.
    2. Lizhen Lin & Walter W. Piegorsch & Rabi Bhattacharya, 2015. "Nonparametric Benchmark Dose Estimation with Continuous Dose-Response Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 713-731, September.
    3. Bhattacharya, Rabi & Lin, Lizhen, 2013. "Recent progress in the nonparametric estimation of monotone curves—With applications to bioassay and environmental risk assessment," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 63-80.
    4. Signe M. Jensen & Felix M. Kluxen & Christian Ritz, 2019. "A Review of Recent Advances in Benchmark Dose Methodology," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2295-2315, October.

    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. Krief, Jerome M., 2017. "Direct instrumental nonparametric estimation of inverse regression functions," Journal of Econometrics, Elsevier, vol. 201(1), pages 95-107.
    2. Bo Hu & Yuan Ji & Kam-Wah Tsui, 2008. "Bayesian Estimation of Inverse Dose Response," Biometrics, The International Biometric Society, vol. 64(4), pages 1223-1230, December.
    3. Dette, Holger & Scheder, Regine, 2008. "A finite sample comparison of nonparametric estimates of the effective dose in quantal bioassay," Technical Reports 2008,05, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Wang Wei & Small Dylan, 2012. "A Comparative Study of Parametric and Nonparametric Estimates of the Attributable Fraction for a Semi-continuous Exposure," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-22, November.
    5. Black, Stephen & Mansouri, H., 1995. "On exact distributions of rank tests for ordered alternatives in block designs," Computational Statistics & Data Analysis, Elsevier, vol. 20(3), pages 265-274, September.
    6. Bhattacharya, Rabi & Lin, Lizhen, 2013. "Recent progress in the nonparametric estimation of monotone curves—With applications to bioassay and environmental risk assessment," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 63-80.
    7. Nilabja Guha & Anindya Roy & Leonid Kopylev & John Fox & Maria Spassova & Paul White, 2013. "Nonparametric Bayesian Methods for Benchmark Dose Estimation," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1608-1619, September.
    8. Ying Yuan & Guosheng Yin, 2011. "Dose–Response Curve Estimation: A Semiparametric Mixture Approach," Biometrics, The International Biometric Society, vol. 67(4), pages 1543-1554, December.
    9. Karunamuni, Rohana J. & Tang, Qingguo & Zhao, Bangxin, 2015. "Robust and efficient estimation of effective dose," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 47-60.
    10. Shi, Ning-Zhong & Jiang, Hua, 1998. "Maximum Likelihood Estimation of Isotonic Normal Means with Unknown Variances," Journal of Multivariate Analysis, Elsevier, vol. 64(2), pages 183-195, February.
    11. Miguel A. Delgado & Juan Carlos Escanciano, 2013. "Conditional Stochastic Dominance Testing," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 16-28, January.
    12. Fernando, W.T.P.S. & Kulatunga, D.D.S., 2007. "On the computation and some applications of multivariate isotonic regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 702-712, October.
    13. Walter W. Piegorsch & Hui Xiong & Rabi N. Bhattacharya & Lizhen Lin, 2014. "Benchmark Dose Analysis via Nonparametric Regression Modeling," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 135-151, January.
    14. Guffey, James M. & Wright, F. T., 1996. "Testing for monotonicity in the intensity of a nonhomogeneous Poisson process," Statistics & Probability Letters, Elsevier, vol. 28(3), pages 195-202, July.
    15. Mansouri, Hossein & Shaw, Carrie, 2004. "Nonparametric multiple comparison procedures for ordered parameters in balanced incomplete blocks," Computational Statistics & Data Analysis, Elsevier, vol. 46(3), pages 593-604, June.
    16. Wei Wang & Dylan S. Small, 2015. "Monotone B-Spline Smoothing for a Generalized Linear Model Response," The American Statistician, Taylor & Francis Journals, vol. 69(1), pages 28-33, February.
    17. Delgado, Miguel A. & Escanciano, Juan Carlos, 2012. "Distribution-free tests of stochastic monotonicity," Journal of Econometrics, Elsevier, vol. 170(1), pages 68-75.
    18. Lizhen Lin & Walter W. Piegorsch & Rabi Bhattacharya, 2015. "Nonparametric Benchmark Dose Estimation with Continuous Dose-Response Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 713-731, September.

    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:eee:stapro:v:80:y:2010:i:23-24:p:1947-1953. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.