On Thu, 27 Apr 2000, Lorenzo Camprini wrote:
> In my set of data I have five indipendent vars and a single
> dependent var. I'm looking for software/method of regression
> using the five indipendent vars like a single variable containing
> the best value of five for every case.
The usual approach, I should think, would be to predict the "dependent"
variable (call it Y) from the five "independent" variables or
"predictors" (call them X1, X2, .., X5); and, possibly, from at least
some of the interactions among X1...X5; using multiple linear regression
(conveniently available in virtually all statistics packages). Is there
a reason for NOT doing that in this case?
There would also appear to be problems in identifying "the best value
of five" in defining the predictor you say you want to create. Not
least of them is the question of whether the five "independent" variables
are in any reasonable sense identical, or parallel, or equivalent. If
none of these terms apply, I don't see how you can possibly do it.
> I'm not very friendly with statistic jargon and I don't
> know if this is a trivial question ...
-- DFB.
------------------------------------------------------------------------
Donald F. Burrill [EMAIL PROTECTED]
348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
MSC #29, Plymouth, NH 03264 603-535-2597
184 Nashua Road, Bedford, NH 03110 603-471-7128
===========================================================================
This list is open to everyone. Occasionally, less thoughtful
people send inappropriate messages. Please DO NOT COMPLAIN TO
THE POSTMASTER about these messages because the postmaster has no
way of controlling them, and excessive complaints will result in
termination of the list.
For information about this list, including information about the
problem of inappropriate messages and information about how to
unsubscribe, please see the web page at
http://jse.stat.ncsu.edu/
===========================================================================
