Multiple regression with dummy variables

[#1]

How can I select intercept in multiple regression?

I want two lines to cross the Y axis in the (0,100) point.

Thanks

Tohar

[#2]

I assume that you selected Analyze > Fit Model to start the multiple regression. A check box is at the center of the bottom of the launch dialog. Select it to remove the intercept from the model

[#3]

This post describes how to use the Fit Y-by-X/Bivariate platform with by()  .... to collect the slopes and intercepts:

Creating-columns-from-Linear-Fit-Constants-slope-intercept 

[#4]

Perhaps more details are needed as I am the third to respond and I have a different take on your question. You said you wanted the lines to go through (0, 100). That is not the same as having the y-intercept of zero. You could use the nonlinear platform to build a model with a fixed y-intercept of 100 and the rest of the linear model to estimate the parameters with that restriction.

Provide a bit more clarity of your situation so that we can better assist you.

[#5]

Oh, thanks, I miss-read this sentence.
In the Fit Y - by - X / Bivariate Platform there is also an option to set the intercept to a fixed value:
Constrain intercept to

[#6]

I'm trying to do a multivariable linear regression. A continuous variable explains -X and a continuous variable is explained -Y and another dummy factor is categorical 0 or 1. I know that the lines should cut the Y-axis at 100 and I want to define this in the model.

 Similar to the solution in the Fit Y by X platform that "hogi" suggested but I have two lines- two groups.

Thank you very much

[#7]

@Tohar , so it sounds like you have an ANCOVA model (one categorical factor C, and one continuous X) and you want to regress Y on these.  Define Y100 = Y-100.  then use Y100 as your response. then the only effect in your model will be C*X, with no intercept. See pic below. Also, in the red triangle pull down menu deselect "Center Polynomials". 

Run this and get the following: And remember Y100 is Y-100. So, when Y100=0, Y=100. You can then get creative with Save Prediction Formula/Graph Builder/etc to get the Y axis back to the raw scale (shift it back up by 100).

[#8]

Thank you very much

I am not about the result I got; the lines cross the Y axis in (0,0) - see attached.

My goal is to check if there is a difference in rate (ie slope) between the two treatment groups. It is not necessary to check whether there is a difference in the intercept, I want to set it both in the model and in the presentation graph at (0,100).

Many thanks!!!!!

Tohar

[#9]

@Tohar  Assuming your model is correct (I have my doubts from looking at your residual plots etc),  the p-value for the parameter estimate and/or in the ANOVA table tells the story (they are equivalent)  If less than 0.05 (that is the "usual" threshold /Type 1 error rate) then you could claim that there is a difference in slope. Strictly speaking, you are testing whether or not there is any difference from the reduced model Y100=0 (i.e, just noise). The p-value says reject the Y100= 0 model in favor of the two slope model (where slope1 = - slope2). 

[#10]

@Tohar . On second thought, use the same model with the interaction (as I said) and Days From Start.(see below). Then assess the equivalence of slopes via the p-value for the interaction parameter estimate. Adding the extra term will give more flexibility wrt the slope estimates (doesn't force slope1 = -slope2).