msg from atul

From: bvatul <bvatul@ufl.edu> Subject: msg from atul Date: Tue, 14 Nov 2000 15:02:11 -0500 Hello All Could someone please clarify my doubts 1. I am using ADVAN3 TRANS4 to fit the observed concentrations of a drug. I have two data sets from two studies; rich (phaseI) as well as sparse (phaseIII). The rich data set could be explained by ADVAN3 using proportional error model. However when I am analysing the sparse data set, in which the patients are administered concurrently many drugs, the model is unable to explain the variability correctly. There are five outliers out of 84 patients where I am observing high weighted residuals value of 15. The dose is given as a short term infusion. Could anyone please share views about how to go with the outliers. I have tried FO as well as FOCE and various error models (Proportional and additive). One more message which I observed was "OCCURS DURING SEARCH FOR ETA AT NONZEROVALUE OF ETA. A ROOT OF THE CHARACTERISTIC EQUATION IS 0 BECAUSE K*K21 IS MUCH SMALLER THAT (K+K12+K21)**2. PERHAPS K OR K21 IS VERY SMALL OR K12 IS VERY LARGE". 2. When I am analysing sparse data set seperately (the model parameterised in terms of Q, CL and V) the values of intercompartmental clearance (Q=6) differs from rich data set (Q=70). I do not have enough points in the distribution phase. Will such a situation lead to this discrepancy. or is it due to any model misspecification. Can I fix the value of Q and its omega which I observed in rich data set to sparse data set and analyse. Will it be meaningful? What is the criterion of fixing omega? Does any one forsee any problem if I analyse sparse and rich data set of the same drug together and later on check for potential covariates. Or should I analyse sparse data set separately. Thanks in advance Atul