R help - Jan 2014 - SE for R-squared

In R package "psychometrics" an estimate of SE of R squared of /sersq
<-
sqrt((4*rsq*(1-rsq)^2*(n-k-1)^2)/((n^2-1)*(n+3))) with n sample size, 
and  k number of parameters if sample size greater than 60 is found. 
Does anyone have a formula for smaller sample size or an exact formula?
I have been through sos - but only found the above?

All best wishes
Troels Ring
Denmark
/

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On Jan 10, 2014, at 12:32 PM, Troels Ring wrote:
> In R package "psychometrics" an estimate of SE of R squared of
/sersq <-
> sqrt((4*rsq*(1-rsq)^2*(n-k-1)^2)/((n^2-1)*(n+3))) with n sample size, 
> and  k number of parameters if sample size greater than 60 is found. 
> Does anyone have a formula for smaller sample size or an exact formula?
> I have been through sos - but only found the above?
This is more of a general statiscs question. You are asked to post such on venue
that encourage such discussion. CrossValidated is one such venue.
> 
> 	[[alternative HTML version deleted]]
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
-- 

David Winsemius
Alameda, CA, USA

Have a look at

http://davegiles.blogspot.ie/2013/10/more-on-distribution-of-r-squared.html

John


On 10 January 2014 20:32, Troels Ring <tring@gvdnet.dk> wrote:
> In R package "psychometrics" an estimate of SE of R squared of
/sersq <-
> sqrt((4*rsq*(1-rsq)^2*(n-k-1)^2)/((n^2-1)*(n+3))) with n sample size,
> and  k number of parameters if sample size greater than 60 is found.
> Does anyone have a formula for smaller sample size or an exact formula?
> I have been through sos - but only found the above?
>
> All best wishes
> Troels Ring
> Denmark
> /
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
John C Frain
Economics Department
Trinity College Dublin
Dublin 2
Ireland
www.tcd.ie/Economics/staff/frainj/home.html
mailto:frainj@tcd.ie
mailto:frainj@gmail.com

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On 12 Jan 2014, at 21:36 , John C Frain <frainj at gmail.com> wrote:
> Have a look at
> 
> http://davegiles.blogspot.ie/2013/10/more-on-distribution-of-r-squared.html
> 
Or head directly for the Wikipedia page for the noncentral beta distribution
(and/or noncentral F). Giles doesn't really do the non-null distribution.

It you really want the mean and SE, you'll need to refresh your knowledge
about confluent hypergeometric functions, though.

I was a bit bemused by Giles' us of the beta distribution of R^2 in the null
case to prove that it is an upwardly biased estimator of zero. I would have
thought that to be rather obvious.

Anyways, as has already been pointed out, 

CrossValidated is -----> over there.

- Peter D.

> John
> 
> 
> On 10 January 2014 20:32, Troels Ring <tring at gvdnet.dk> wrote:
> 
>> In R package "psychometrics" an estimate of SE of R squared
of /sersq <-
>> sqrt((4*rsq*(1-rsq)^2*(n-k-1)^2)/((n^2-1)*(n+3))) with n sample size,
>> and  k number of parameters if sample size greater than 60 is found.
>> Does anyone have a formula for smaller sample size or an exact formula?
>> I have been through sos - but only found the above?
>> 
>> All best wishes
>> Troels Ring
>> Denmark
>> /
>> 
>>        [[alternative HTML version deleted]]
>> 
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>> 
> 
> 
> 
> -- 
> John C Frain
> Economics Department
> Trinity College Dublin
> Dublin 2
> Ireland
> www.tcd.ie/Economics/staff/frainj/home.html
> mailto:frainj at tcd.ie
> mailto:frainj at gmail.com
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com