hi Siwei, you should include the BLOQ data as they are, i.e. negative. Any other approach would decrease precision (e.g. M3 likelihood-based) and/or induce bias (e.g. LLOQ/2 or LLOQ=0). I've done some simulations on this a while ago to show this ( http://page-meeting.org/pdf_assets/2413-PAGE_2010_poster_LLOQ_v1.pdf), but it should be intuitive too. best regards, Ron
---------------------------------------------- Ron Keizer, PharmD PhD Dept. of Bioengineering & Therapeutic Sciences University of California San Francisco (UCSF) ---------------------------------------------- On Thu, Oct 2, 2014 at 2:10 PM, siwei Dai <ellen.siwei...@gmail.com> wrote: > Dear NM users: > > I have a dataset where some of the concentrations are reported as negative > values. I believe that the concentrations were calculated using a standard > curve. > > My instinct is to impute all the negative values to zero, but worry that > it will introduce bias. > > A 2nd thought is using the absolute value of the lowest (negative) > concentration as LLOQ. All the concentrations below LLOQ will be treated as > zero. By doing this, some positive and negative values both will be zero > out which will help to cancel some of the unevenness that the 1st method > may introduce. > > I believe that the 2nd method is better but wonder if there is any other > better way to do it. Any comments will be greatly appreciated. > > Thank you in advance. > > Siwei >
