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D-optimal Designs for Logistic Regression in Two Variables

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mODa 8 - Advances in Model-Oriented Design and Analysis

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

In this paper locally D-optimal designs for the logistic regression model with two explanatory variables, both constrained to be greater than or equal to zero, and no interaction term are considered. The setting relates to dose-response experiments with doses, and not log doses, of two drugs. It is shown that there are two patterns of D-optimal design, one based on 3 and the other on 4 points of support, and that these depend on whether or not the intercept parameter β 0 is greater than or equal to a cut-off value of −1.5434. The global optimality of the designs over a range of β 0 values is demonstrated numerically and proved algebraically for the special case of the cut-off value of β 0.

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References

  • Atkinson A (2006) Response Surface Methodology and Related Topics, World Scientific, New Jersey, chap 8: Generalized linear models and response transformation

    Google Scholar 

  • Atkinson A, Donev A (1992) Optimum Experimental Designs. Clarendon Press, Oxford

    MATH  Google Scholar 

  • Atkinson A, Haines L (1996) Handbook of Statistics, vol 13, Elsevier, Amsterdam, chap 11: Designs for nonlinear and generalized linear models

    Google Scholar 

  • Chernoff H (1953) Locally optimal designs for estimating parameters. Ann Math Statist 24:586–602

    MathSciNet  Google Scholar 

  • Jia Y, Myers R (2001) Optimal experimental designs for two-variable logistic regression models. Preprint

    Google Scholar 

  • Kupchak P (2000) Optimal designs for the detection of drug interaction. PhD thesis, University of Toronto, Toronto

    Google Scholar 

  • Sitter R, Torsney B (1995) Optimal designs for binary response experiments with two design variables. Statistica Sinica 5:405–419

    MATH  MathSciNet  Google Scholar 

  • Torsney B, Gunduz N (2001) Optimum Design 2000, Kluwer, Dordrecht, chap 24: On optimal designs for high dimensional binary regression models

    Google Scholar 

  • Wang Y, Myers R, Smith E, Ye K (2006) d-optimal designs for poisson regression models. J Statist Plann Inference 136:2831–2845

    Article  MATH  MathSciNet  Google Scholar 

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© 2007 Physica-Verlag Heidelberg

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Haines, L.M., Kabera, G., Ndlovu, P., O’Brien, T.E. (2007). D-optimal Designs for Logistic Regression in Two Variables. In: López-Fidalgo, J., Rodríguez-Díaz, J.M., Torsney, B. (eds) mODa 8 - Advances in Model-Oriented Design and Analysis. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-1952-6_12

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