Re: Rate constants..are dead?

From: "James Wright" <damage128@hotmail.com> Subject: Re: Rate constants..are dead? Date: Tue, 28 Nov 2000 13:06:41 -0000 Dear nmusers, I am very pro-half-life (for linear models) because to me it is interpretable and not just by pharmacokineticists. In the population context, the distributional assumptions are of some interest however. Physiologically, the half-life is a ratio of volume and clearance. Positively contrained ratios will tend to be lognormal. As half-life and ke are reciprocally related, then if one is lognormally distributed so is the other (reciprocalisation corresponds to reflection on the log-scale) but with different mean and variance. I do not intend to contradict Vladimirs practical advice, as lognormality may be a better approximation on the time-scale. I have never tried it so I do not know. The lognormality of such parameters are discussed in detail in Julious SA and Debarnot CAM. Why are pharmacokinetic data summarized by arithmetic means? Journal of Biopharmaceutical Statistics 2000; 10: 55-71. However, if you come to model a covariate on half-life (for example, if half-life was the parameter of clinical interest) then you should bear in mind that your distributional assumptions now describe perturbations about the model predictions. If you have chosen a model linear on the log-scale then the model will be equivalent for rate constants. Otherwise, it won't and neither will your distributional assumptions. Regards, James