## RE: [APBR_analysis] Michael: A minor point ...

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• ... From: jsm_44092 [mailto:tpr42345@aol.com] Sent: Friday, January 02, 2004 10:16 PM ... The terminology may be discipline-dependent. In econometrics, I
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-----Original Message-----
From: jsm_44092 [mailto:tpr42345@...]
Sent: Friday, January 02, 2004 10:16 PM

>When you state "multivariate regression" I assume you mean one
>dependent variable with multiple explanatory variables. Correct?
>That is "multiple regression". Multivariate regression, which is
>performed by running the univariate regressions, is when there is
>more than one dependent variable. The two terms are often used
>interchangeably in certain literature, but they are not the same.

The terminology may be discipline-dependent. In econometrics,
I usually see the term "multivariate regression". See, e.g. MIT's
calendar for the syllabus for its undergrad econometrics class, 14.32:
http://ocw.mit.edu/OcwWeb/Economics/14-32EconometricsSpring2003/Calendar/index.htm

After the usual review of probability and statistical inference, the
real meat of the course starts with lectures 6 - 11, which start
with the simple "bivariate regression" model (although I usually use
the term "univariate regression", and evidently you do also) and then
move to "Introduction to multivariate regression".

What you seem to be calling "multivariate regression" -- models with more
than one dependent variable, in which several regressions are run -- are
called "simultaneous equation models" in econometrics (the regressions
however need not be, and usually are not, univariate ones). This same
progression of "univariate regression", "multivariate regression", and
"simultaneous equation models" is e.g. used by Wiley to describe the
contents of one of its econometrics books:
http://www.wiley.com/WileyCDA/WileyTitle/productCd-0471802603.html

On the other hand, the econometrics class the Univ. of Virginia
evidently uses the terminology that you're advocating: "univariate
regression" being the second item on its schedule and "multiple
regression" the fifth item: