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07-23-2016 09:31 AM

I would like to detect a outliers and multicollinearity for my regression (both linear and logistic) analysis. Appreciate if someone guide me through options/procs for that.

Thanks in advance!

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Solution

07-24-2016
02:09 AM

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07-23-2016 10:14 PM

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07-23-2016 10:39 AM

What's your definition of an outlier?

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07-23-2016 12:26 PM

I don't have any definition for outlier. Just I want to see the

observations which is far away from normal distribution.

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observations which is far away from normal distribution.

##- Please type your reply above this line. Simple formatting, no

attachments. -##

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07-23-2016 03:59 PM

Your questions are too broad. They're chapters in text books.

If your trying to learn statistical theory and SAS have you taken the first statistic e-course from SAS? It's free.

There's also a ton of videos on topics related to specific statistical procedures.

http://support.sas.com/training/tutorial/

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07-23-2016 12:46 PM

Suggestions:

- Make that two separate topics (questions)
- Formulate each question as a problem such as "I have the following dataset and would like to know if obs 12 is an outlier relative to this regression model, how can I do that?"

PG

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07-23-2016 04:53 PM

For linear regression you can use the ROBUSTREG procedure. The procedure has algorithms that automatically flag outliers. The documentation contains several Getting Started examples. I suggest you start with the examples and then move on to the "Details" section if you want to understand the details about how an observation is classified as an outlier.

There is not an analogous "robust" procedure for logistic regression. However, there are still techniques for detecting potential outliers in almost every SAS procedure. The technique is to use regression diagonostic plots.

For example, in PROC REG you can use the INFLUENCE option on the MODEL statement and look at the ODS graphics to assess observations that are highly influential in the model. See the section of the doc titled "Influence Statstics".

You can do something similar for logistic regression. The LOGISTIC procedure contains many diagnostic plots. As Reeze says, a full explanation is lengthy, but start with the doc example "Logistic Regression diagnostics", which shows how to use the INFLUENCE option and the diagnostic plots.

Solution

07-24-2016
02:09 AM

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07-23-2016 10:14 PM