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Optimization in a multivariate generalized linear model situation

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  • Mukhopadhyay, S.
  • Khuri, A.I.

Abstract

The purpose of this article is to find the settings of the factors which simultaneously optimize several mean responses in a multivariate generalized linear model (GLM) environment. The generalized distance approach, initially developed for the simultaneous optimization of several linear response surface models, is adapted to this multivariate GLM situation. An application of the proposed methodology is presented in the special case of a bivariate binary distribution resulting from a drug testing experiment concerning two responses, namely, the efficacy and toxicity of a particular drug combination. One of the objectives of this application is to find the dose levels of two drugs that simultaneously maximize their therapeutic effect and minimize any possible toxic effects. A second application is presented in the case of a multivariate gamma distribution.

Suggested Citation

  • Mukhopadhyay, S. & Khuri, A.I., 2008. "Optimization in a multivariate generalized linear model situation," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4625-4634, June.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:10:p:4625-4634
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    References listed on IDEAS

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    1. B. Nebiyou Bekele & Yu Shen, 2005. "A Bayesian Approach to Jointly Modeling Toxicity and Biomarker Expression in a Phase I/II Dose-Finding Trial," Biometrics, The International Biometric Society, vol. 61(2), pages 343-354, June.
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    Cited by:

    1. Nuno Costa & Paulo Fontes, 2020. "Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods," Sustainability, MDPI, vol. 12(18), pages 1-19, September.

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