Date:         Thu, 1 Dec 2005 21:22:57 -0500
Reply-To:     Peter Flom <flom@NDRI.ORG>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Peter Flom <flom@NDRI.ORG>
Subject:      Re: Multiple Imputation in a Narrow Range
Comments: To: topkatz@MSN.COM
Content-Type: text/plain; charset=US-ASCII

>>> Talbot Michael Katz <topkatz@MSN.COM>  >>> wrote
<<<
There was a presentation at the most recent NYASUG meeting about robust
regression, and the speaker was talking about dealing with various data
issues.  One issue in the example data (from a real experiment) was as
follows.  A measurement is done with a machine; readings are positive
numbers, and the results above the machine calibration threshhold are
lognormally distributed.  Readings below the machine calibration
threshhold are just reported as "< 0.4" or "< 0.6" (depending on how the
machine was calibrated that particular day).  The speaker had simply
converted such values to 0.2 or 0.3, respectively, but invited
suggestions
from the crowd.  One audience member (and SAS-L denizen) mentioned
multiple imputation, and this idea led to a side discussion after the
talk
finished.  These values are not true missing values; they are somewhere
between 0 and the calibration threshhold, but they just can't be
measured
with the same accuracy as readings above the calibration threshhold, so
there are no accurate values within that range.  How would you handle
such
values?  (Discarding is not an option.)
>>>

The 'audience member and SAS-L denizen was me.
Nice to meet you, TMK, and put a face to the name.

It was also an interesting discussion, and I look forward to more
discussion of it
here......

Peter