Imbalance or incomplete data, SASophylistic view [🇷 for BE/BA]
Dear Yung-ying,
The heading you cited is from Proc GLM
.
Under Proc MIXED there are no SSq nor MSq.
This is because the REML estimation method does not rely on SSq's and their decomposition.
The shown point estimates and 90% CI's are from the difference between Least square means.
Here is my code for Proc GLM / mixed (to play around with, it seems you have access to "The power to know"):
❝ still has ANOVA Table with PROC MIXED?
The heading you cited is from Proc GLM

Under Proc MIXED there are no SSq nor MSq.
This is because the REML estimation method does not rely on SSq's and their decomposition.
❝ What 90%CI method did you use?
The shown point estimates and 90% CI's are from the difference between Least square means.
Here is my code for Proc GLM / mixed (to play around with, it seems you have access to "The power to know"):
ODS output LSMeandiffCL=ratios; *<- this saves the 90% CIs;
Proc GLM data=BEBAC24long;
class formul period subject sequence;
model logCmax=formul period sequence subject(sequence);
random subject(sequence) /test;
lsmeans formul/cl pdiff alpha=0.1;
run; quit;
*log diff R-T is calc. because of lexicographic order, but we need T-R;
Data ratios;
set ratios;
point=Exp(-difference);
lower=exp(-upperCL);
upper=exp(-lowerCL);
run;
ODS output Diffs=ratiosMixed;*<- this saves the 90% CIs;
Proc mixed data=BEBAC24long;
class formul period subject sequence;
model logCmax=formul period sequence /ddfm=satterth;
random subject(sequence) /subject=subject;
lsmeans formul/cl diff alpha=0.1;
run;
—
Regards,
Detlew
Regards,
Detlew
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