Since the goal is to look at a logarithmic relationship, I'm wondering
if using glm with a log-link for a normal family wouldn't be helpful.
That way you don't need to worry about 0 values.
Tony
Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Feiveson,
Alan H. (JSC-SK311)
Sent: Wednesday, January 07, 2009 11:54 AM
To: [email protected]
Subject: st: RE: RE: RE: RE: how to deal with a censored and skewed
regressor?
If there were other X-variables, one way (probably not the best) would
be to use multiple imputation. More generally, some sort of structural
model that relates Y to true X and includes the censoring mechanism
could be estimated (ha!). I suspect there are econometric models out
there that do this sort of thing - possibly even already programmed in
Stata.
AL F.
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Nick Cox
Sent: Wednesday, January 07, 2009 1:06 PM
To: [email protected]
Subject: st: RE: RE: RE: how to deal with a censored and skewed
regressor?
And how would you do that? Other than knowing that c.i.s and P-values
are not as good as they seem, what difference does this knowledge make
to what you do?
Nick
[email protected]
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Feiveson,
Alan H. (JSC-SK311)
Sent: 07 January 2009 18:27
To: [email protected]
Subject: st: RE: RE: how to deal with a censored and skewed regressor?
Nick wrote: "If you regard such a regressor as error-free, as one
usually does, then I am not clear that procedure need otherwise be
affected."
But if the variable (say X )is censored, then it's real value is unknown
except for an upper or lower bound and there is error ,hence bias in the
regression parameter estimates if X is used as is. So in mbaier's case,
if X is really censored at zero, that means it's true value is some
negative number. This needs to be taken into account in the estimation.
Al Feiveson
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Nick Cox
Sent: Wednesday, January 07, 2009 12:09 PM
To: [email protected]
Subject: st: RE: how to deal with a censored and skewed regressor?
(x - r(min)) / (r(max) - r(min))
does not yield missing when r(min) is 0 unless x is missing or r(max) is
also zero. But that's neither here or there. The above is just a linear
rescaling of a variable and will thus leave skewness unchanged.
Skewness of a regressor is not itself fatal to anything.
Censoring of a regressor is something to take account of in
interpretation. If you regard such a regressor as error-free, as one
usually does, then I am not clear that procedure need otherwise be
affected.
Nick
[email protected]
mbaier
I tried to transform it according to ln(skewed variable), but my
regressor has a lots of values at zero, for which ln is not defined. I
also tried to create an index like I=100*(x-r(min))/(r(max)-r(min)),
which again leads to many missings (due to many x's being zero).
What can I do?
Besides, do I have to account for the censoring of my regressor? If so,
what can I do?
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