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RE: Re: st: Detecting Outliers


From   "b. water" <barleywater@hotmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: Re: st: Detecting Outliers
Date   Wed, 3 May 2006 17:41:20 +0000

Along the line of Nick Cox's suggestion and Ronan's advice - you could generate BMI (body mass index) variable that would unify height and weight followed by a histogram. These ought to identify the extremes.

Regards,
bw

----------------------------------------
> From: rconroy@rcsi.ie
> Subject: Re: st: Detecting Outliers
> Date: Wed, 3 May 2006 15:31:14 +0100
> To: statalist@hsphsun2.harvard.edu
> 
> On 2 Beal 2006, at 14:27, Raphael Fraser wrote:
> 
> > my objective is simple to locate potential outliers then cross check
> > with patient records to ensure that the information is legitimate.
> > error free.
> 
> You will have to look at multivariate outliers, then. A height of  
> 160cm is believable as is a weight of 120 Kg, but in combination they  
> suggest error (but do not prove it). You need to think of groups of  
> measures which, together, define outliers.
> 
> =========
> Ronán Conroy
> rconroy@rcsi.ie
> +353 (0) 1 402 2431
> +353 (0) 87 799 97 95
> www.flickr.com/photos/ronanconroy
> 
> 
> 
> 
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