[R] bootstrapping in regression

[Charles C. Berry]

On Fri, 30 Jan 2009, Stephan Kolassa wrote:

> Hi Thomas,
>
> Thomas Mang schrieb:
>>
>>  I have a question here: I am not sure if I understand your 'fit the full
>>  model ... to the permuted data set'. Am I correct to suppose that once the
>>  residuals of the reduced-model fit have been permuted and added back to
>>  the fitted values, the values obtained this way (fitted + permuted
>>  residuals) now constitute the new y-values to which the full model is
>>  fitted? Is that correct ?
>
> It is. Look at section 2.2, "Permutation of Residuals under the Reduced 
> Model" here:
>
> Anderson, M. J. & Legendre, P. An empirical comparison of permutation methods 
> for tests of partial regression coefficients in a linear model. Journal of 
> Statistical Computation and Simulation, 1999, 62, 271-303
>
>>  Do you know if this procedure is also valid for a mixed-effects model ?
>
> That's a good question... if you find out anything about this, please let me 
> know.

There are various kinds of residuals in mixed effects models. But mostly 
they are not what you want.

What you need are the type of residuals used in the section on 
significance tests in Beran and Srivastava:


@article{beran1985bta,
   title={{BOOTSTRAP TESTS AND CONFIDENCE REGIONS FOR FUNCTIONS OF A 
COVARIANCE MATRIX1}},
   author={Beran, R. and Srivastava, M.S.},
   journal={The Annals of Statistics},
   volume={13},
   number={1},
   pages={95--115},
   year={1985}
}

HTH,

Chuck

>
> HTH,
> Stephan
>
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Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901