I have a pretty basic question that I cannot find the solution to....
When performing a polynomial fit as shown below...
Is there a way to get the resulting polynomial in the typical form like that below?
y = c0 + c1*x + c2*x^2
Im sure there is a clever reason for giving fit results in the JMP default form...please enlighten me as to why.
Thx,
Rory
JMP automatically centers variables when higher order terms are added to the model. This practice is recommended to reduce the collinearity among predictors to, in turn, reduce the variance inflation. (x^2 is highly collinear with x otherwise.)
There are two ways to get the form that you want:
Hope one of these ways is satisfactory.
JMP automatically centers variables when higher order terms are added to the model. This practice is recommended to reduce the collinearity among predictors to, in turn, reduce the variance inflation. (x^2 is highly collinear with x otherwise.)
There are two ways to get the form that you want:
Hope one of these ways is satisfactory.
Hi Mark,
Thanks for your explanation. Is there any reference (e.g. paper, book) that we can use to justify the centering practice for higher order terms? Look forward to your recommendation.
Claire
The practice of centering regressor variables is covered and recommended in practically all textbooks about regression analysis. Many softwares do not provide this option or if they do, it is not the default, however. JMP decided to make it the default many years ago when there are higher order terms in the linear model. It makes no difference when all the terms are first order.
Here is a commonly cited source specifically about regression problems, including collinearity:
Belsley, D. A., Kuh, E., and Welsch, R. E. (1980). Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: John Wiley & Sons.