Abstract
Models for enzyme inhibition form a family of extensions of the Michaelis-Menten model to two explanatory variables. We present four-point locally Ds-optimum designs for discriminating between competitive and non-competitive models of inhibition and explore the sensitivity of the designs to the values of the two nonlinear parameters in the model. We evaluate combinations of pairs of locally optimum designs. A robust design is found with six support points that has high minimum and average efficiencies over all considered parameter values.
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Atkinson, A.C., Bogacka, B. (2013). Robust Experimental Design for Choosing Between Models of Enzyme Inhibition. In: Ucinski, D., Atkinson, A., Patan, M. (eds) mODa 10 – Advances in Model-Oriented Design and Analysis. Contributions to Statistics. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00218-7_2
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DOI: https://doi.org/10.1007/978-3-319-00218-7_2
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