IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v55y1999i2p437-444.html
   My bibliography  Save this article

Optimum Experimental Designs for Multinomial Logistic Models

Author

Listed:
  • Silvio S. Zocchi
  • Anthony C. Atkinson

Abstract

No abstract is available for this item.

Suggested Citation

  • Silvio S. Zocchi & Anthony C. Atkinson, 1999. "Optimum Experimental Designs for Multinomial Logistic Models," Biometrics, The International Biometric Society, vol. 55(2), pages 437-444, June.
  • Handle: RePEc:bla:biomet:v:55:y:1999:i:2:p:437-444
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.1999.00437.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Robert K. Tsutakawa, 1980. "Selection of Dose Levels for Estimating a Percentage Point of a Logistic Quantal Response Curve," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 25-33, March.
    2. A. C. Atkinson & C. G. B. Demetrio & S. S. Zocchi, 1995. "Optimum Dose Levels When Males and Females Differ in Response," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(2), pages 213-226, June.
    3. M. J. R. Healy, 1968. "Algorithm as 6: Triangular Decomposition of a Symmetric Matrix," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 17(2), pages 195-197, June.
    4. Y. Zhu & D. Krewski & W. H. Ross, 1994. "Dose‐Response Models for Correlated Multinomial Data from Developmental Toxicity Studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(4), pages 583-598, December.
    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. Idais, Osama, 2020. "Locally optimal designs for multivariate generalized linear models," Journal of Multivariate Analysis, Elsevier, vol. 180(C).
    2. Andreas Falke & Harald Hruschka, 2017. "Setting prices in mixed logit model designs," Marketing Letters, Springer, vol. 28(1), pages 139-154, March.
    3. Peter F. Thall & Randall E. Millikan & Peter Mueller & Sang-Joon Lee, 2003. "Dose-Finding with Two Agents in Phase I Oncology Trials," Biometrics, The International Biometric Society, vol. 59(3), pages 487-496, September.
    4. Bodunwa, O. K. & Fasoranbaku, O. A., 2020. "D-optimal Design in Linear Model With Different Heteroscedasticity Structures," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 9(2), pages 1-7, March.
    5. Guiteras, Raymond P. & Levine, David I. & Polley, Thomas H., 2016. "The pursuit of balance in sequential randomized trials," Development Engineering, Elsevier, vol. 1(C), pages 12-25.
    6. Linda M. Haines & Inna Perevozskaya & William F. Rosenberger, 2003. "Bayesian Optimal Designs for Phase I Clinical Trials," Biometrics, The International Biometric Society, vol. 59(3), pages 591-600, September.

    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. Linda M. Haines & Inna Perevozskaya & William F. Rosenberger, 2003. "Bayesian Optimal Designs for Phase I Clinical Trials," Biometrics, The International Biometric Society, vol. 59(3), pages 591-600, September.
    2. Molenberghs, Geert & Declerck, Lieven & Aerts, Marc, 1998. "Misspecifying the likelihood for clustered binary data," Computational Statistics & Data Analysis, Elsevier, vol. 26(3), pages 327-349, January.
    3. Dette, Holger & Pepelyshev, Andrey & Wong, Weng Kee, 2008. "Optimal designs for dose finding experiments in toxicity studies," Technical Reports 2008,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Andrew S. Allen & Huiman X. Barnhart, 2002. "Joint Models for Toxicology Studies with Dose‐Dependent Number of Implantations," Risk Analysis, John Wiley & Sons, vol. 22(6), pages 1165-1173, December.
    5. D. Krewski & Y. Zhu, 1995. "A Simple Data Transformation for Estimating Benchmark Doses in Developmental Toxicity Experiments," Risk Analysis, John Wiley & Sons, vol. 15(1), pages 29-39, February.
    6. Zacks, S. & Rogatko, A. & Babb, J., 1998. "Optimal Bayesian-feasible dose escalation for cancer phase I trials," Statistics & Probability Letters, Elsevier, vol. 38(3), pages 215-220, June.
    7. Hanemann, W. Michael & Kanninen, Barbara, 1996. "The Statistical Analysis Of Discrete-Response Cv Data," CUDARE Working Papers 25022, University of California, Berkeley, Department of Agricultural and Resource Economics.
    8. Per A. Brodtkorb, 2006. "Evaluating Nearly Singular Multinormal Expectations with Application to Wave Distributions," Methodology and Computing in Applied Probability, Springer, vol. 8(1), pages 65-91, March.
    9. Jaakko Reinikainen & Juha Karvanen, 2022. "Bayesian subcohort selection for longitudinal covariate measurements in follow‐up studies," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(4), pages 372-390, November.
    10. Yangxin Huang, 2003. "Selection of number of dose levels and its robustness for binary response data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1135-1146.
    11. Hui Li & Robert Malkin, 2000. "An approximate Bayesian up-down method for estimating a percentage point on a dose-response curve," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 579-587.
    12. Daniel Krewski & Robert Smythe & Karen Y. Fung, 2002. "Optimal Designs for Estimating the Effective Dose in Developmental Toxicity Experiments," Risk Analysis, John Wiley & Sons, vol. 22(6), pages 1195-1205, December.
    13. Karen Y. Fung & Leonora Marro & Daniel Krewski, 1998. "A Comparison of Methods for Estimating the Benchmark Dose Based on Overdispersed Data from Developmental Toxicity Studies," Risk Analysis, John Wiley & Sons, vol. 18(3), pages 329-342, June.

    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:bla:biomet:v:55:y:1999:i:2:p:437-444. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.