The word prove has at least two meanings. One is to test (as in
the proof of the pudding is in the eating). It is not unreasonable
to guess that Darwin might have been using the word in this somewhat
archaic sense.
Thom
Stu wrote:
Was Darwin's statement It has been experimentally proved
In article [EMAIL PROTECTED],
Roland Pesch [EMAIL PROTECTED] wrote:
HI,
I'm trying to perform factor analysis on mosses from 1028 moss
monitoring sites, each of which was chemically anaylsed on 20 heavy
metal elements. All of these samples do not follow a normal distribution
pattern, they are
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Is it possible that multicollinearity can force a correlation that
does not exist?
I have a very large sample of n=5,000
and have found that
disease= exposure + exposure + exposure + exposure R^2=0.45
where all 4 exposures are the exact same exposure in different units
like ug/dL or mg/dL or
Dear EdStat-ers,
Here is an announcement of a new IASE journal, sent by Brian Phillips,
Past-President of the IASE.
Jackie Dietz
Statistics Education Research Journal
The International Association for Statistical Education
Apologies if this is not the appropriate forum to ask such a question,
but I'm wondering what should the entering statistics PhD student know
before starting grad school (note: not biostatistics or genetics).In
particular, mastery of what disciplines prior to entry is essential
and would anyone
I'm curious to know why you're using the same exact exposure in different
units. I've included a dichotomized version of a continuous exposure
variable to look at potential threshold effects, but I've never heard of
anyone doing what you've described.
At 08:28 AM 2/5/02 -0800, Wuzzy wrote:
Cengiz:
I'd say pure and applied mathematics by which I mean real analysis,
linear algebra and numerical methods.
--
Rodney Sparapani Medical College of Wisconsin
Sr. Biostatistician Patient Care Outcomes Research (PCOR)
[EMAIL PROTECTED]
Title: RE: can multicollinearity force a correlation?
Is it possible that multicollinearity can force a correlation that
does not exist?
I have a very large sample of n=5,000
and have found that
disease= exposure + exposure + exposure + exposure R^2=0.45
where all 4 exposures are
On 4 Feb 2002 16:14:11 -0800, [EMAIL PROTECTED] (Wuzzy) wrote:
In biostatistical studies, either version of beta is pretty worthless.
Generally speaking.
If I may be permitted to infer a reason:
if you have
bodyweight= -a(drug) - b(exercise) + food
Then the standardized
You made a model with the exact same exposure in different units,
which is something that no one would do,
Hehe, translation is don't post messages until you've thought them
through.
Anyway, turns out that the answer to my question is No..
Multicollinearity cannot force a correlation. It
In my own defense:
I was asking a simple question:
will highly correlated cause an irregularly high R^2.
My answer to my own question is no it can't..
No-one here was able to give me this answer and I believe it is
correct: if your sample is large enough,(as mine is) then no,
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