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Posted 10-30-2023 10:55 PM
(385 views)

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

1 ACCEPTED SOLUTION

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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 ...

7 REPLIES 7

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More explanation is needed.

What are the variables X Z1 Z2 XZ1 XZ2 Z1Z2?

--

Paige Miller

Paige Miller

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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 |

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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 ...

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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).

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Paige Miller

Paige Miller

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

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Thanks so much for your support...

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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.

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Paige Miller

Paige Miller

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