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iressa1313
Calcite | Level 5

Hello,

 

I am performing a multi-linear regression analysis with 1 dichotomous and 1 continuous regressor and there is a significant interaction.

 

How can I assess coincidence from the PROC REG procedure in SAS?

I have read that ANCOVA is the appropriate method but what if I am only given the ANOVA and parameter estimates output?

 

Here is my current thought process:  if I fit the model for each value of the dichotomous variable then the lines will differ and hence, are not coincident. Am I thinking about this correctly? 

5 REPLIES 5
Reeza
Super User
What’s your definition of coincidence in this contex?
iressa1313
Calcite | Level 5

When two lines lie directly on top of eachother

PGStats
Opal | Level 21

If interaction is significant then ANCOVA is not appropriate. Significant interaction means that the two lines do not have the same slope. They may cross at some point but will diverge as you move away from that point. So they definitively don't coincide.

PG
Rick_SAS
SAS Super FREQ

@iressa1313 wrote:

1. I am performing a multi-linear regression analysis with 1 dichotomous and 1 continuous regressor and there is a significant interaction.

 

2. How can I assess coincidence from the PROC REG procedure in SAS?

3. I have read that ANCOVA is the appropriate method but what if I am only given the ANOVA and parameter estimates output?

 

4. Here is my current thought process:  if I fit the model for each value of the dichotomous variable then the lines will differ and hence, are not coincident. Am I thinking about this correctly? 


I think there are some issues that need to be clarified:

1. If you have a dichotomous regressor, you want to use PROC GLM with a CLASS statement, not PROC REG.

2. When you fit a model with PROC GLM, you can test whether the interaction term is significant. You can also test whether the coefficient for the dichotomous parameter is significant.

3. I am confused by this question. You say "what if I am only given the ANOVA and parameter estimates output." Do you have the data or not? If you only have the parameter estimates (as a table), then please post it.

4. I would fit a model that includes a CLASS variable (the dichotomous regressor) rather than fit two models, especially if you think there is interaction. To understand the difference between using a CLASS statement and fitting two different models, study the article "The difference between CLASS statements and BY statements in SAS"

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