someone else can blast me if this is not correct but i think that 2
step procedure only gives the same answer as the regular regression if
X1 and
X2 perfectly uncorrelated. If they are at all correlated, then what john
pointed out messes the procedure up. i was asked that question on
an interview a long time ago and the question i always wondered but
never asked was why someone would want to do that ? so, here goes:
why do you want to do that ?
On Tue, Jul 8, 2008 at 6:25 PM, rlearner309 wrote:
Thanks for the reply.
I am awared of the difference, but can I do regression by steps at
all? I
am not feeling comfortable about it.
John Sorkin wrote:
Be very careful!
When regression is performed by steps, you often will not get the
same
results as you would get from a single multivariable regression. The
explanation for this is not simple, but a simplified explanation is
that
when you do your first regression,
y=f(x1)
all the total variance that can be accounted for is sucked up by x1
leaving little varinace to be accounted for by your second
regression,
residuals=f(x2). In contrast when you perform a multivariable
regression,
y=f(x1,x2) the total variance is proportioned between x1 and x2.
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)
rlearner309 <[EMAIL PROTECTED]> 7/8/2008 8:53 AM >>>
I saw this type of models in some of my company projects.
To simplify:
Y is regressed on X1 and X2. But the regression is done by two
steps: First Y is regressed on X1 with intercept, and the residuals
from the
first
step are used to regress on X2, without the constant. The reason to
do so
is some observations have X1 data but do not have X2, so I guess the
person
wants to use as much information as he can to get the coef. for X1,
and
then
use part of the residuals (that have X2 data) to catch what is left
to be
explained by X2.
But my concern is, should we consider the correlation between X1 and
X2? If
residuals from the first step are used, then X1 effect has been
removed. Then what does it really mean by regressing residuals on X2,
which has
some
X1 effect correlated with?? should X2 be adjusted by X1, too (regress
X2
on
X1 and use the residuals)?
What if both X1 and X2 are dummy variables? Dummy variables can have
a
meaningful correlation, too, right?
Thanks a lot!
--
View this message in context:
http://www.nabble.com/Can-I-do-regression-by-steps--tp18338562p18338562.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the
posting guide
http://www.R-project.org/posting-guide.html and provide commented,
minimal, self-contained, reproducible code.
Confidentiality Statement:
This email message, including any attachments, is for
th...{{dropped:6}}
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
View this message in context:
http://www.nabble.com/Can-I-do-regression-by-steps--tp18338562p18350475.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
