Hi all,
I am trying to model a continous variable across the time with several timepoints (0,3,6,9 and 12 months) and 2 predictors.
One is continuous (5 and 10) and the other is categorical (A, B and C) and for each of the combinaison I have 30 replicates.
The relation between Y and the time is not expeted to be linear. My main concern is to study the behavior of Y along the time and see if the 2 predictors included in the experiment have an influence.
Which statistical methodology/SAS procedure would you recommend?
Here is what I've used so far (SAS CODE):
ODS GRAPHICS ON;
PROC GLM DATA=STUDY PLOTS=ALL;
CLASS Component;
MODEL Y = Timepoint Timepoint*Timepoint Component FillingCoefficient FillingCoefficient*Timepoint Timepoint*Component / SOLUTION;
OUTPUT OUT=STUDY_results PREDICTED=pred RESIDUAL=res COOKD=Dcook RSTUDENT=rstud;
RUN;
Thanks in advance.
Cédric.
I am trying to model a continous variable across the time with several timepoints (0,3,6,9 and 12 months) and 2 predictors.
One is continuous (5 and 10) and the other is categorical (A, B and C) and for each of the combinaison I have 30 replicates.
The relation between Y and the time is not expeted to be linear. My main concern is to study the behavior of Y along the time and see if the 2 predictors included in the experiment have an influence.
Which statistical methodology/SAS procedure would you recommend?
Here is what I've used so far (SAS CODE):
ODS GRAPHICS ON;
PROC GLM DATA=STUDY PLOTS=ALL;
CLASS Component;
MODEL Y = Timepoint Timepoint*Timepoint Component FillingCoefficient FillingCoefficient*Timepoint Timepoint*Component / SOLUTION;
OUTPUT OUT=STUDY_results PREDICTED=pred RESIDUAL=res COOKD=Dcook RSTUDENT=rstud;
RUN;
Thanks in advance.
Cédric.