Re: BQL values, version 3

Date: Sat, 31 Jul 1999 00:08:58 +0100 (GMT) From: "J.G. Wright" <J.G.Wright@newcastle.ac.uk> Subject: Re: BQL values, version 3 There are two things to bear in mind when dealing with BQL observations. 1) A BQL observation does not necessarily mean that the "true" value is below BQL. Sometimes observations above BQL will be recorded as below BQL because of assay variability etc. Thus the support for a BQL observation on the likelihood should actually extend above BQL. Exactly how much is hard to determine. 2) Some account of the uncertainty induced by these censored obervations has to be acknowledged. One approach to this is multiple imputation, where you create numerous datasets with different random values(generated from a sensible model) and analyse each dataset separately. Then combine across datasets to get an average value and confidence intervals which acknowledge this uncertainty (definitely superior to a single imputation). This is debatably a discrete analogue of an EM-type analogue, with the advantage that it can be easily implemented in NONMEM. Of course, the choice of imputation model is crucial. However for regulatory submission, a conservative method (with large variability) is probably the best option. James Wright