1) are the two lines coincident? 2) are the slopes different? 3) are the intercepts different?

[swBuenoLopez]

I want to answer the following questions:

• are the lines coincident?
• are the slopes different?
• are the intercepts different?

For that, I have used the following piece of code:

PROC REG DATA=ALL;

        MODEL Y = X Z1 Z2  XZ1 XZ2 Z1Z2;

        INTERCEP: TEST Z1, Z2;

        SLOPE: TEST XZ1, XZ2;

        COINCID: TEST Z1, Z2, XZ1, XZ2;

        RUN;

How can I interpret the results?

Comments will be deeply appreciated...

Best,

Santiago

[PaigeMiller]

More explanation is needed.

What are the variables X Z1 Z2 XZ1 XZ2 Z1Z2?

[swBuenoLopez]

X is a continuous explanatory variable; Y is a continuous dependent variable, Z1 and Z2 are dichotomous variables. An example of the data is:

Y	X	Z1	Z2
0.38448	11134.94	1	0
0.42872	10280.34	1	0
0.45391	12595.40	1	0
0.26954	7461.27	1	0
0.49276	13352.59	1	0
1.09706	33692.40	1	0
0.31529	8987.04	1	0
0.20629	5190.80	1	0
0.49011	15962.34	1	0
0.23585	6454.96	1	0
0.54901	14717.25	1	0
0.26269	7757.72	1	0
0.62173	14394.44	1	0
0.60383	18041.02	1	0
0.47756	13406.98	1	0
0.44168	11272.19	1	0
0.09205	2349.10	1	0
0.32221	8780.78	1	0
0.19188	5586.24	1	0
0.19467	4797.40	1	0
0.08793	2121.80	1	0
0.13247	3744.60	1	0
0.22353	5683.04	1	0
0.09343	2175.01	1	0
0.47902	13764.63	0	1
0.21821	5703.75	0	1
0.08321	1954.22	0	1
0.15906	4490.16	0	1
0.50418	15138.00	0	1
0.08847	2178.00	0	1
0.16686	4471.20	0	1
0.17571	4435.76	0	1
0.27287	7337.30	0	1
0.05631	1362.18	0	1
0.13135	3717.12	0	1
0.41391	11741.91	0	1
0.13025	3207.24	0	1
0.34055	10097.38	0	1
0.32904	8126.60	0	1
0.47509	12354.75	0	1
0.80383	23064.00	0	1
0.66650	18758.08	0	1

[ballardw · Accepted solution]

Sometimes a picture is worth a lot of tests:

proc sgplot data=have;
   reg x=x y=y/group=z1;
run;

Or set ods graphics one and use the PLOTS statement of Proc Reg or Proc GLm or ...

[PaigeMiller]

I'm surprised you don't get an error from PROC REG since Z1 and Z2 are perfectly correlated. But I really don't use PROC REG much any more.

I would do this in PROC GLM (in which case Z2 is not needed)

proc glm data=have;
    class z1;
    model y=x z1 x*z1;
run; quit;

If the statistical test of the effect of Z1 is statistically significant then the intercepts are different. If the effect of X*Z1 is significant, then the slopes are different. I might want to think about this a little more, but if the tests for both Z1 and X*Z1 are both not significant, then the lines are coincident (except for random noise).

[swBuenoLopez]

Thanks so much, ladies and gentlemen...your support is deeply appreciated!!!!

[swBuenoLopez]

Thanks so much for your support...

[PaigeMiller]

So in your original problem statement, you were performing statistical testing in PROC REG. Then you mark correct the answer which just draws plots. I don't think plots is the correct answer, although it may be very helpful to have a plot, there is no statistical testing going on.