The need for objective design of pharmacokinetic experiments aimed at model discrimination is argued. A sequential design strategy based on information theory is outlined. The characteristics of this strategy and its applicability to pharmacokinetic experiments is examined by means of computer simulated experiments. The limitation of the technique are discussed and alternative approaches outlined.
Expressions were derived for the computation of regression model posterior probabilities under a number of assumptions regarding the form of the uniform parameter prior probability density function. It was demonstrated that some of these forms may lead to a bias in the model posterior probabilities. The variance known and unknown situations were considered under both homoscedastic and heteroscedastic conditions. Bias of the model posterior probabilities may partly explain the unstable behaviour reported by previous workers.
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