Comparing three different slopes between three regression lines

Hi all,

I hope the thread is in it's place.
I wanted to compare slopes between three different simple regression lines. The three data sets have the same x (time) and y (measured value) variables but each data set have gone through a different treatment and so the intercept and the slopes are different.
The null hypothesis is that the treatment did not have any effect on the rate of the change in y. The alternative hypothesis is that different treatments have caused different rates. Which basically means I don't care much about the intercept and I want to compare the different b's.

How would you do that using spss?
Thank you
(I added a picture to make things clearer)



Less is more. Stay pure. Stay poor.
Was treatment assignment randomized? Tell us more about whether there were 3 unique samples or how observations were assigned to treatments.
Treatments were assigned randomly.
It's a basic science experiment in which I took cells from mice and put them through 3 different treatments and then checked one of their function (the y axis) in different time periods. every 30 minutes I checked for the groups. I expected the treatment to effect the rate of the change in y and so it seems (to slopes are different) but I want to check the significance of it.


Well-Known Member
You could try a General Linear Model with a group*time interaction. If the interaction is significant there is a difference somewhere and a post hoc test will show where it is.
The cells were a mixture from few mice that went through the same conditioning and after separated for three groups randomly the treatment applied


Less is more. Stay pure. Stay poor.
If you had a sample and randomized them to treatment you could use @katxt suggestion. However, I am still confused by the origins of the samples and if they care comparable between treatment arms. Also, what is your sample size?