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Robust regression in JMP
Hi. I found outliers by detecting Robust Outlier analysis in unidimensional data at a time and Robust Outlier analysis in unidimensional data at a time. I wanna to prevent the influences of outliers in multiple linear regression analysis. Should I perform robust regression analysis? If so, how to do it?
Or I can detect Hats, studentized Residuals, or Cooks' D distance? If not so bad result, I can also read Standarded least Squares results. Thanks!
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Re: Robust regression in JMP
I will point you to the Statistics Index. There you will find pointers to the Help pages for Robust Regression, and also an actual Example of a Robust Regression run in JMP.
Help=>Statistics Index
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Re: Robust regression in JMP
Hi, txnelson,
Your insights were invaluable and helped me tremendously in my analysis. Thank you for your time and effort.
However, I have come across a new challenge in my research, and I was hoping you could provide some guidance. In my current study, I am trying to predict a dependent variable using multiple independent variables simultaneously. While I have successfully included these variables in the analysis, I realized that the results only present bivariate relationships and do not report the model fit of the regression.
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Re: Robust regression in JMP
For multiple linear analyses you need to look into the Multivariate Platform, or the Fit Model Platform.
I suggest that you take the time to read the Discovering JMP documentation available under the Help pull down menu. You may also want to explore the JMP Tutorials.