Question about computing 90% CI w data from 2 separate studies [General Sta­tis­tics]

posted by BEQool  – 2024-10-18 14:03 (16 d 11:13 ago) – Posting: # 24240
Views: 447

Hello J,

❝ I am going to try the following codes later today.


Did you try it? How did it go?

❝ What do you think?

PROC MIXED data=BEdata;

CLASSES SUBJECT TRT;

MODEL logval = TRT/ DDFM=SATTERTH;

RANDOM TRT/TYPE=FA0(2) SUB=SUBJECT G;

REPEATED/GRP=TRT SUB=SUBJECT;

ESTIMATE 'T vs. R' TRT 1 -1/CL ALPHA=0.1;

lsmeans TRT/ cl alpha=0.1; * <-- for parallel design studies, alpha=0.1;

ods output lsmeans=lsmeans;         * Least Squares means Output;

ods output covparms=covparms;       * Covariance output;

ods output estimates=ests;          * Estimate of differences between treatments;


I dont use SAS a lot and am therefore not an experienced user but I think you dont need statements in blue because you have a parallel design with just one factor Treatment.

And if you want to estimate T vs. R and have it coded like that, you should switch "1 -1" to "-1 1", otherwise with code "1 -1" you will get R vs. T and not T vs. R.
If you have it coded A vs. C (like in your first post) then "1 -1" is correct (it depends on the alphabetical order).

Regards
BEQool

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