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st: RE: Query about bootstrapping and R-squared


From   Nick Riches <nick.riches@newcastle.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Query about bootstrapping and R-squared
Date   Wed, 7 Dec 2011 11:49:47 +0000

Many thanks for the advice!

Nick

>-----Original Message-----
>From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
>statalist@hsphsun2.harvard.edu] On Behalf Of Nick Riches
>Sent: 07 December 2011 09:35
>To: statalist@hsphsun2.harvard.edu
>Subject: st: Query about bootstrapping and R-squared
>
>Hi
>
>This may be more of a general stats query than a Stata query, but any pointers
>would be most appreciated.
>
>I'm running a commonality analysis (identifying unique and shared contributions
>to R-squared). The reviewers have commented on the lack of power / overfitting
>(2 predictors, 23 observations), so I thought I'd run a bootstrapped version to
>compensate for overfitting. The trouble is, the R-squared from the bootstrapped
>regression is identical to the R-squared in the non-bootstrapped regression. In
>addition the value of R-squared is completely unaffected by the number of reps.
>
>I can't see why this is the case. Surely each time the program randomly
>resamples, a different regression line is drawn, parameters and residuals will vary
>and therefore R-squared will vary?
>
>Thanks
>
>Nick Riches
>
>P.S. Syntax = bootstrap, reps(100): regress x y z
>
>
>
>Dr Nick Riches
>Lecturer in Speech and Language Pathology
>Education Communication and Language Sciences (ECLS)
>King George VI building
>Queen Victoria Road
>Newcastle University
>NE1 7RU
>
>Tel - 0191 222 6518
>
>(International +44 191 222 6518)
>
>
>
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