Hi,
I am running a linear mixed model with random intercept using glimmix to estimate the blood pressure over time of participants in a randomized control trial. I use a spline function to account for the sharp changes in blood pressure I observed over a treatment period, and my study question is if the blood pressure (bp) trajectory differ by treatmentgroup and exposureofinterest.
Here is my SAS code:
proc glimmix data=data order=formatted;
class visit release_id year treatmentgroup covariate1 covariate2 covariate3;
effect spl=spline(year/basis=bspline degree=3 KNOTMETHOD=list(1,4) details);
model bp= spl|treatmentgroup|exposureofinterest
covariate1 covariate2 covariate3
/solution;
random intercept/type=un sub=release_id;
store model;
run;
proc plm source=model;
effectplot slicefit(x=y sliceby=exposureofinterest plotby=treatmentgroup)/clm;
run;
I can visualize the effect using the effectplot function, however, I wonder if there's a way to output the effect estimate at each cross-section of time, ie. year=1 year=2? (is it possible to use the estimate and contrast function? but since year is included in the spline but not as a variable in the model, how do I specify time?
I also tried using the score function to output one unit of change in exposureofinterst by treatmentgroup, hoping to obtain just the effect estimate using the following code. But I am not getting any predicted lclm uclm. Is there anything wrong with my code?
data template;
do intercept=0;
do &x._0_L2=1;
do SEX=0;
do B_AGEGROUP=0;
do RACE=0;
do B_edu=0;
do B_income=0;
do B_married=0;
do B_ALC_DAY=0;
do B_smoke=0 ;
do DASH=0;
do assign="Lifestyle";
do y=0 to 10 by 0.5;
output;
end;
end;
do assign="Placebo";
do y=0 to 10 by 0.5;
output;
end;
end;
end;
end;
end;
end;
end;
end;
end;
end;
end;
end;
end;
run;
data template;
set template;
*calculate the predicated values for each value of t;
proc plm restore=plot2;
score data=template out=estimate predicted=predicted lclm=lclm uclm=uclm;
run;
Thanks.
