PROC Mixed Multiple Contrast statements

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PROC Mixed Multiple Contrast statements

I have 5 treatments (lets call A, B, C, D, E). I want to compare:

A to B

A to average of B, C, D, E

linear (not including A)

quadratic (not including A)

I wrote the following contrast statements, but it seems like A is being used in my linear & quadratic contrasts.

CONTRAST 'A vs B'                           trt  1  -1 0  0  0;

CONTRAST 'A vs ave of B to E'         trt  4 -1 -1 -1 -1 ;

CONTRAST 'Linear B to E'                 trt  0 -3 -1  1  3;

CONTRAST 'Quadratic B to E'            trt  0 -1  3 -3  1;

How do you make sure that in the linear & quadratic contrasts, trt A is not being used?

Any help verifying these statements would be appreciated.


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‎03-11-2013 07:50 AM
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Posts: 2,655

Re: PROC Mixed Multiple Contrast statements

Posted in reply to AgReseach7

These look like they should be OK.  What indication do you have that trt A is being used?  To check, add the /e option, and the L matrix coefficients will be displayed.

Steve Denham

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‎03-11-2013 07:50 AM
Respected Advisor
Posts: 2,655

Re: PROC Mixed Multiple Contrast statements

Posted in reply to AgReseach7

These look like they should be OK.  What indication do you have that trt A is being used?  To check, add the /e option, and the L matrix coefficients will be displayed.

Steve Denham

Contributor
Posts: 40

Re: PROC Mixed Multiple Contrast statements

Posted in reply to SteveDenham

It seems like A is being used, because when I exclude A from the data and run linear/quadratic contrasts, .

Trt diet A is much different than the other 4 trt diets. Trt A is a traditional diet and was mainly included to compare

A to B.  Thus, I think is OK to run the analysis, only using A and B.  Then re-run the analysis using only B to E?

Then, just write the paper as Trial 1 and Trial 2?

See any problems using trt B in both analysis?

Again, your time/knowledge is much appreciated.

Travis

Respected Advisor
Posts: 2,655

Re: PROC Mixed Multiple Contrast statements

Posted in reply to AgReseach7

The analysis should reflect the design.  Separate analyses leads to reduced power, and the lack of indepence in the comparisons (A to B, B to the others) is lost when you do separate analyses.

When you exclude A, and run the contrasts (assuming that you rewrite them so that ordering is correct), the p value is going to change.  You change both the residual error estimate and the degrees of freedom available for the comparison.

Steve Denham

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