Hi, I have a numerical measurement taken over time (7 timepoints) for two groups (diseased - n=14 and control - n=31). There are a few missing values at some timepoints. As below, I arranged the timepoints into one column and by timepoint (though, since the most recent update, I can't get day14 to = 1 etc). proc sort data=one; by horse status age; run; proc transpose data=one out =two; by horse status age; var day14 day28 day42 day56 day70 day84 day98; run; ***need to divide by 40 b/c EPG dilution factor!!!; data three; set two; time = _LABEL_; if _NAME_ = 'day14' then time = 1; if _NAME_ = 'day28' then time = 2; if _NAME_ = 'day42' then time = 3; if _NAME_ = 'day56' then time = 4; if _NAME_ = 'day70' then time = 5; if _NAME_ = 'day84' then time = 6; if _NAME_ = 'day98' then time = 7; COL1ct = round(COL1/40); Keep horse age status time COL1 COL1ct; run; proc sort; by time; run; Looking at distribution, igaussian had the lowest AIC score. Using proc glimmix, with the code below, to determine differences between the variable of interest (COL1ct) and groups (status), significance was shown at certain timepoints and overall. proc glimmix data =three ABSPCONV=0.00001;
class status time horse;
model COL1ct = status age/ dist = igaussian noint solution cl;
random time / residual type=cs subject=horse*time;
by time;
**Parms (0.8189) (2.2);
run; This didn't compare slopes and I wanted to know if the diseased group had a significantly steaper slope than the control group. I used the below code but I'm not confident that this is correct for what I want. It would be great if someone can let me know if I'm on the right track or if I should change anything. The results printout is pasted below **comparing slope elevations https://support.sas.com/kb/24/177.html ;
proc glimmix data=three ABSPCONV=0.00001;
class status time;
model COL1ct = status*time/ dist = igaussian noint solution cl;
run;
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