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MCPMod: An R Package for the Design and Analysis of Dose-Finding Studies

Author

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  • Bornkamp, Björn
  • Pinheiro, José
  • Bretz, Frank

Abstract

In this article the MCPMod package for the R programming environment will be introduced. It implements a recently developed methodology for the design and analysis of dose-response studies that combines aspects of multiple comparison procedures and modeling approaches (Bretz et al. 2005). The MCPMod package provides tools for the analysis of dose finding trials, as well as a variety of tools necessary to plan an experiment to be analyzed using the MCP-Mod methodology.

Suggested Citation

  • 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).
    • Handle: RePEc:jss:jstsof:v:029:i07
    DOI: http://hdl.handle.net/10.18637/jss.v029.i07
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    Cited by:

    1. Philip N. Newsome & Arun J. Sanyal & Guy Neff & Jörn M. Schattenberg & Vlad Ratziu & Judith Ertle & Jasmin Link & Alison Mackie & Corinna Schoelch & Eric Lawitz, 2023. "A randomised Phase IIa trial of amine oxidase copper-containing 3 (AOC3) inhibitor BI 1467335 in adults with non-alcoholic steatohepatitis," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Md Abu Manju & Math J. J. M. Candel & Gerard J. P. van Breukelen, 2019. "SamP2CeT: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials," Computational Statistics, Springer, vol. 34(1), pages 47-70, March.
    3. Qiqi Deng & Xiaofei Bai & Dacheng Liu & Dooti Roy & Zhiliang Ying & Dan‐Yu Lin, 2019. "Power and sample size for dose‐finding studies with survival endpoints under model uncertainty," Biometrics, The International Biometric Society, vol. 75(1), pages 308-314, March.
    4. Christian Ritz & Florent Baty & Jens C Streibig & Daniel Gerhard, 2015. "Dose-Response Analysis Using R," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-13, December.
    5. Frank Schaarschmidt & Christian Ritz & Ludwig A. Hothorn, 2022. "The Tukey trend test: Multiplicity adjustment using multiple marginal models," Biometrics, The International Biometric Society, vol. 78(2), pages 789-797, June.
    6. 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.

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