st: RE: RE: RE: Measures of association for a small sample

["Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>]

The interpretation seems to be that the sample is from a population of years.  In that case i'd agree.

________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of David Radwin [dradwin@mprinc.com]
Sent: Tuesday, January 10, 2012 9:49 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: RE: Measures of association for a small sample

Good point. For differing views on whether significance tests are
appropriate for population data, please see:

http://andrewgelman.com/2011/10/how-do-you-interpret-standard-errors-from-
a-regression-fit-to-the-entire-population/

or the shorter URL: http://tinyurl.com/7xa2pxo

David
--
David Radwin
Research Associate
MPR Associates, Inc.
2150 Shattuck Ave., Suite 800
Berkeley, CA 94704
Phone: 510-849-4942
Fax: 510-849-0794

www.mprinc.com


> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
> statalist@hsphsun2.harvard.edu] On Behalf Of Lachenbruch, Peter
> Sent: Tuesday, January 10, 2012 7:32 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: RE: Measures of association for a small sample
>
> If you have the entire population, why do you need significance tests?
> Isn't the measure sufficient?
>
> ________________________________________
> From: owner-statalist@hsphsun2.harvard.edu [owner-
> statalist@hsphsun2.harvard.edu] On Behalf Of Francisco Rowe
[frowe@ucn.cl]
> Sent: Tuesday, January 10, 2012 4:35 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Measures of association for a small sample
>
> Hi,
>
> Sorry for taking advantage of statalist for this -I am trying to measure
> the association between two variables with a reduced number of
> observations (13) which constitutes my entire population.
>
> I have utilised pairwise correlation coefficients (pwcorr) and
regression
> using an Iteratively Reweighted Least Squares (IRLS) estimation (rreg)
(on
> cross-sectional data). However, given some of the assumptions of these
> measures, the results can be questioned. For this reason, I would like
to
> implement some additional tests or measures on my data.
>
> Would it be possible to have some guidance on this?
> Are regressions based on IRLS useful in this context?
> Which non-parametric measure can it be useful?
>
> Thanks in advance.
>
> Francisco.

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