IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v103i483y2008p1225-1237.html
   My bibliography  Save this article

Optimal Designs for Dose-Finding Studies

Author

Listed:
  • Dette, Holger
  • Bretz, Frank
  • Pepelyshev, Andrey
  • Pinheiro, José

Abstract

No abstract is available for this item.

Suggested Citation

  • Dette, Holger & Bretz, Frank & Pepelyshev, Andrey & Pinheiro, José, 2008. "Optimal Designs for Dose-Finding Studies," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1225-1237.
    • Handle: RePEc:bes:jnlasa:v:103:i:483:y:2008:p:1225-1237
    as

    Download full text from publisher

    File URL: http://pubs.amstat.org/doi/abs/10.1198/016214508000000427
    File Function: full text
    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.

    Citations

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


    Cited by:

    1. repec:jss:jstsof:29:i07 is not listed on IDEAS
    2. 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.
    3. Dette, Holger & Pepelyshev, Andrey & Shpilev, Piter & Wong, Weng Kee, 2009. "Optimal designs for estimating critical effective dose under model uncertainty in a dose response study," Technical Reports 2009,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Amir Ali Nasrollahzadeh & Amin Khademi, 2022. "Dynamic Programming for Response-Adaptive Dose-Finding Clinical Trials," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1176-1190, March.
    5. Wiens, Douglas P., 2021. "Robust designs for dose–response studies: Model and labelling robustness," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    6. Dette, Holger & Pepelyshev, Andrey & Zhigljavsky, Anatoly, 2014. "‘Nearly’ universally optimal designs for models with correlated observations," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1103-1112.
    7. Eric Gibson & Frank Bretz & Michael Looby & Bjoern Bornkamp, 2018. "Key Aspects of Modern, Quantitative Drug Development," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(2), pages 283-296, August.
    8. Yu, Jun & Meng, Xiran & Wang, Yaping, 2023. "Optimal designs for semi-parametric dose-response models under random contamination," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    9. Jiajing Xu & Guosheng Yin & David Ohlssen & Frank Bretz, 2016. "Bayesian two-stage dose finding for cytostatic agents via model adaptation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(3), pages 465-482, April.
    10. Dette, Holger & Pepelyshev, Andrey & Shpilev, Piter & Wong, Weng Kee, 2009. "Optimal designs for estimating critical effective dose under model uncertainty in a dose response study," Technical Reports 2009,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    11. Bornkamp, Björn & Pinheiro, José & Bretz, Frank, 2009. "MCPMod: An R Package for the Design and Analysis of Dose-Finding Studies," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i07).
    12. Holger Dette & Laura Hoyden & Sonja Kuhnt & Kirsten Schorning, 2017. "Optimal designs for thermal spraying," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 53-72, January.
    13. Idais, Osama, 2020. "A note on locally optimal designs for generalized linear models with restricted support," Statistics & Probability Letters, Elsevier, vol. 159(C).
    14. Dette, Holger & Holland-Letz, Tim, 2008. "A geometric characterization of c-optimal designs for heteroscedastic regression," Technical Reports 2008,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    15. McGree, J.M., 2017. "Developments of the total entropy utility function for the dual purpose of model discrimination and parameter estimation in Bayesian design," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 207-225.
    16. Min-Jue Zhang & Rong-Xian Yue, 2021. "Optimal designs for homoscedastic functional polynomial measurement error models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 485-501, September.
    17. Bretz, Frank & Dette, Holger & Pinheiro, José, 2008. "Practical considerations for optimal designs in clinical dose finding studies," Technical Reports 2008,22, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    18. Peter F. Thall & Hoang Q. Nguyen & Sarah Zohar & Pierre Maton, 2014. "Optimizing Sedative Dose in Preterm Infants Undergoing Treatment for Respiratory Distress Syndrome," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 931-943, September.

    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:bes:jnlasa:v:103:i:483:y:2008:p:1225-1237. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    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.