CODEWITHSUNDEEP
sascontrastmixed
Michael
Michael

Reputation: 75

Comparing variable combinations using contrast or estimate in SAS

So, this should be an easy one, but I've always been garbage at contrasts, and the SAS literature isn't really helping. We are running an analysis, and we need to compare different combinations of variables. For example, we have 8 different breeds and 3 treatments, and want to contrast breed 5 against breed 7 at treatment 1. The code I have written is:

proc mixed data=data;
class breed treatment field;
model ear_mass = field breed field*breed treatment field*treatment breed*treatment;
random field*breed*treatment;
estimate "1 C0"
breed 0 0 0 0 1 0 -1 0 breed*treatment 0 0 0 0 1 0 0 0 -1 0 0; 
run;

What exactly am I doing wrong in my estimate line that isn't working out?

Upvotes: 0

Views: 2427

Answers (2)

user4962951
user4962951

Reputation:

Alas, you must tell SAS, it can't tell you.

You are right, it is easy to make an error. It is important to know the ordering of factor levels in the interaction, which is determined by the order of factors in the CLASS statement. You can confirm the ordering by looking at the order of the interaction lsmeans in the LSMEANS table.

To check you can compute the estimate of the contrast by hand using the lsmeans. If it matches, then you can be confident that the standard error, and so the inferential test, are also correct.

The LSMESTIMATE is a really useful tool, faster and much less prone to error than defining contrasts using model parameters.

Upvotes: 0

user4962951
user4962951

Reputation:

Your contrast statement for this particular comparison must also include coefficients for breed*field.

When defining contrasts, I recommend starting small and building up. Write a contrast for breed 5 at time 1 (B5T1), and check its value against its lsmean to confirm that you've got the right coefficients. Note that you have to average over all field levels to get this estimate. Likewise, write a contrast for B7T1. Then subtract the coefficients for B5T1 from those for B7T1, noting that the coefficients for some terms (e.g., treatment*field) are now all zero.

An easier alternative is to use the LSMESTIMATE statement, which allows you to build contrasts using the lsmeans rather than the model parameters. See the documentation and this paper Kiernan et al., 2011, CONTRAST and ESTIMATE Statements Made Easy:The LSMESTIMATE Statement

Upvotes: 1

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