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Re: st: Factor analysis and winsorizing/Outlier
From
Maarten Buis <[email protected]>
To
[email protected]
Subject
Re: st: Factor analysis and winsorizing/Outlier
Date
Mon, 25 Nov 2013 12:16:07 +0100
The best thing to do is figure out why that observation is so special.
For example, your observations are hospitals, you mainly have regional
hospitals and your outlier is the only academic hospital. After that
you can make an informed decision on how best to include that
observation in your analysis.
-- Maarten
On Mon, Nov 25, 2013 at 12:10 PM, Florian Christian Esser
<[email protected]> wrote:
> Hi Nick,
> thanks for your answer.
> What other things to are there? I am particularly worried about one
> outlier, that is in the range of "4" whereas most other results are based
> around "0". Sample size is 88.
>
> Thanks again
> Florian
>
>> I don't think there is any "should" here that comes on tablets of stone.
>>
>> If you are worried about outliers, there are many things you can do,
>> but if Winsorizing raw data is not enough to produce good results,
>> then further Winsorizing on what factor analysis produces is likely to
>> be going further down the wrong road.
>> Nick
>> [email protected]
>>
>>
>> On 25 November 2013 08:26, Florian Christian Esser
>> <[email protected]> wrote:
>>> Hi everyone,
>>>
>>> I am using an exploratory factor analysis with three factors to derive a
>>> strategy construct based on secondary data.
>>>
>>> If I am winsorizing ma data, how should I proceed? Do I winsorize the
>>> input factors, do I winsorize the resulting construct, do I winsorize at
>>> both stages?
>>>
>>> Thanks a lot
>>> Florian
>>>
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>
>
> *
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--
---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany
http://www.maartenbuis.nl
---------------------------------
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