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Re: st: A reference for "how many independent variables one regression can have?"


From   Richard Goldstein <richgold@ix.netcom.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: A reference for "how many independent variables one regression can have?"
Date   Fri, 13 Dec 2013 11:01:53 -0500

This is often heard/said and is discussed in a number of places (e.g.,
Harrell's book on "Regression Modeling Strategies" on p. 61

however, one implication of this simple statement is that it is
acceptable to estimate a one-predictor model with and N of 10; I don't
agree and would suggest a different rule (don't remember where I have
seen this) such as 50 plus 10/predictor

note that in any version of the rule, predictor should be read as
"canditate" predictors at the start of the modeling process, not the
final number of predictors

Rich

On 12/13/13, 10:50 AM, Ariel Linden wrote:
> Hi All,
> 
> I came across a statement in a book I am using to teach a class on
> evaluation that says "a common rule of thumb is that 1 independent variable
> can be added for every 10 observations." (it goes on to say that this
> depends on multicollinearity and desired level of precision). The book does
> not provide a reference for this statement.
> 
> Does someone know of a reference for this ratio, or perhaps a different
> ratio?
> 
> Thanks!
> 
> Ariel
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