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Jun 15, 2015 2:56 PM
(7834 views)

Hello everybody,

I'm looking for a solution to regress a bivariate data set with a cubic spline regression which has exactly 15 knots. It would be great if someone has a solution for me!

Greetings

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Hello and thanks for your answer! Exactly something like that, but the question is, does lambda represent the amount of knots for my cubic spline?

Edit// Ok I have read now, that your suggestion is a smoothing spline. Smoothing splines are not calculating with knots instead you have penalty function with the factor lambda. So the question is, is there another function in JMP that I can calculate the splines with knots?

By the way is there a nice feature how I can extract the formula of the spline regression and calculate "new" height values by just input the weight values?

**Edit// I think I found a solution. The knotted spline effect should be fine for me, it is hidden under Analyze->FitModel->Attributes**

**To extract formulas and calculate new values, just click on the red red triangle->save columns->prediction formula**

**In the next step just write down the new x-values in the same column were the old x-values are already. The predicted values are displayed in the new column!**

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Re: cubic spline regression

Something like this

Bivariate**(**

Y**(** :height **)**,

X**(** :weight **)**,

Fit Spline**(** **15**, **{**Line Color**(** **{****208**, **64**, **86****}** **)}** **)**

**)**;

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Hello and thanks for your answer! Exactly something like that, but the question is, does lambda represent the amount of knots for my cubic spline?

Edit// Ok I have read now, that your suggestion is a smoothing spline. Smoothing splines are not calculating with knots instead you have penalty function with the factor lambda. So the question is, is there another function in JMP that I can calculate the splines with knots?

By the way is there a nice feature how I can extract the formula of the spline regression and calculate "new" height values by just input the weight values?

**Edit// I think I found a solution. The knotted spline effect should be fine for me, it is hidden under Analyze->FitModel->Attributes**

**To extract formulas and calculate new values, just click on the red red triangle->save columns->prediction formula**

**In the next step just write down the new x-values in the same column were the old x-values are already. The predicted values are displayed in the new column!**

Highlighted
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I see the option of cubic splines is available in JMP at graph builder when you test the moderating effect of a categorical variable on the effect of a categorical variable to the outcome which happens to be... you guessed it...also categorical variable. Does this make sense? Is that possible?

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Re: cubic spline regression