How to determine whether to remove a generated outlier or not in stepwise regression?

Dear Friends, I have developed a stepwise regression model. I am getting a outlier. I need to know the effective weight of the outlier so that I came to understand weather I need to remove it or my model will play good without removing it. In summary, I want to calculate adjusted R2 value with and without outlier.Can you please help

Answer 1

[Greg Heath]

My approach:

 1. Use zscore (you can also use mapst) to standarize all variables to   
    zero-mean/unit-variance.
 2. Use minmax to find the extrema of each variable
 3. Consider all variables outside of [ -3, 3 ] as being outliers which 
    may have to be removed or modified.
 4. Plot all variables which have outliers
 5. Look at the plots and use judgement regarding one of the following choices:
     a. leave it in
     b. reduce the absolute value to 3 or another value of choice
     c. remove it 
 6. When reporting the results 
     a. Explain the process 
     b. Compare the result with one or more of the considered alternatives.

Hope this helps.

Thank you for formally accepting my answer

Greg

[Ajay Goyal]

Sounds very interesting. Could you please elaborate your explanation with an example as being a BioMechanical Research student, I am new to statistics. Please enlighten me further with your guidance

[Greg Heath]

I prefer that

1. You contaminate an example

help nndatasets

2. Attempt to code and apply my algorithm.

3. Post your results

I will comment on your result.

Greg