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st: SE of linear prediction: Use only SE of slope coefficient(s), or also that of the constant?
From
Jen Zhen <[email protected]>
To
[email protected]
Subject
st: SE of linear prediction: Use only SE of slope coefficient(s), or also that of the constant?
Date
Wed, 1 Dec 2010 13:55:02 +0100
Dear listers,
I have estimated Y = A + (B1*X1 + B2*X2 + B3*X3) + (C1*Z1 + C2*Z2+C3*Z3)+eps.
The X are a set of mutually exclusive dummies, and the Z are another
set of mutually exclusive dummies.
Now I want to use these estimated coefficients to compute the average
Y for the three different X cases, keeping Z fixed at any one of its
values, for simplicity say when all Z are zero.
I do this simply by computing A+B1, and similarly for the other
constellations of X.
But I'm unsure what the correct standard error for this is:
Can I simply take the standard error of B1, or do I need also need to
add that of the constant A, as well as the covariance between the
estimated coefficients A and B1?
Many thanks,
JZ
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