Independent of whether your result converges to the true slope, you will have inferential problems as your estimator will not be normally distributed.
John
John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
>>> Jim Silverton <[log in to unmask]> 12/3/2011 12:51 PM >>>
Hello all,
I am interested in doing the following. I have a simple linear regression
problem: Y = a + bX + e where e are errors not necessarily. Now the truth
is that the true slope is between 0 and 1. But my regression equation gives
me a slope that can be either be negative, or positive. So I truncate the
slope, meaning if I get a negative value for the slope, I use 0 and if I
get a positive value greater than 1, I use 1.
My question is this are there any papers around that has this proof for
this type of truncation of the slope? I am looking for a proof that the
trimmed slope that I am using actually converges to the true slope.
--
Thanks,
Jim.
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