Posted by
Art Kendall on
Apr 16, 2012; 3:36pm
URL: http://spssx-discussion.165.s1.nabble.com/Detecting-outliers-when-to-stop-tp5642233p5644223.html
I did not see the original post so cannot CC the OP.
The usual answer is _before removing the first one_.
In my experience having a value flagged as an "outlier" only means that
you should look at it more closely.
In addition to Cook's distance for influential values, doing <data>
<identify unusual cases> is a much better approach to locating data to
check more carefully.
many times users worry unnecessarily about extreme values.
I concur with Bruce that we need more info to give better feedback.
Why are extreme values a problem for you?
What kind of analysis do you have in mind?
Are the extreme values in independent variables, dependent variables, or
covariates?
How many IVs, DVs, covariates are there in your data?
Often clearly stating the substantive questions you are trying to answer
enable list members to give better feedback.
Art Kendall
Social Research Consultants
On 4/16/2012 10:34 AM, Bruce Weaver wrote:
> noxeon wrote
>> So I have detected some outliers in my data and removed them, however when
>> I removed them all, new ones appeared in bloxplot, should I keep removing
>> until there is none or just once is enough?
>>
> What's the variable (or variables)? Have you ruled out data entry errors?
>
> What kind of analysis are you doing, some kind of regression model? If so,
> I'd be more concerned about multivariate outliers and influential points
> than univariate outliers. Cook's distance is one well-known measure of
> influence you could look at.
>
> HTH.
>
>
> -----
> --
> Bruce Weaver
>
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Art Kendall
Social Research Consultants