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Fitting Different Slopes Common Intercepts
Hi - i am unsure how to fit a regression model with different slopes BUT a common Interecpt.
Assume Y=response, GROUP (2-levels), TIme (Covariate)
Kind regards, Vince
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Re: Fitting Different Slopes Common Intercepts
You can do this in Fit Y by X: Y=response, X=time. After the plot, Group by GROUP. Then use Fit Special and constrain the intercept to 0.
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Re: Fitting Different Slopes Common Intercepts
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Re: Fitting Different Slopes Common Intercepts
If you also want to estimate the common intercept, try this approach.
- Select Analyze > Fit Model.
- Click the red triangle at the top left and de-select Center Polynomials.
- Select the response column and click Y.
- Select the time and group columns and click Macros, then select Factorial to Degree.
- Select the group effect and click Remove.
- JMP will ask you to if it should remove all terms with this column. Click No.
- Click Run.
- JMP will warn you about a missing effect. Click Continue.
In general, we would keep the group effect in the model to maintain the model hierarchy. But that leads to a unique or different intercept for each group. This way you will get estimates and tests for the common intercept and unique group slopes.
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Re: Fitting Different Slopes Common Intercepts
Thanks! I made up 40 because it looked good (better than zero, anyway).
edit: adding an image. Left is fit y by x, center is fit model. Right is illustrating how to get the slopes from fit model.
Getting the slopes from Fit Model
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Re: Fitting Different Slopes Common Intercepts
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Re: Fitting Different Slopes Common Intercepts
Fit model does give the intercept and the two slopes in a single step. The picture is comparing the easy-to-read output in fit y by x with the parameters returned by fit model. I puzzled it out by comparing them; I hope @Mark_Bailey is watching in case I've misinterpreted something.
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Re: Fitting Different Slopes Common Intercepts
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Re: Fitting Different Slopes Common Intercepts
I copied it from fit model to @dale_lehman answer, instead of the zero he suggested or the 40 I initially guessed. If you start with fit model rather than fit y by x, you get parameters for both lines without copying the numbers.
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