Hello, I am new to statistics and even more new to programing (studying health sciences). I am currently working on a project with a set of longitudinal data with 7 repeated time measures (YEARS0-YEARS6). The outcome is the MWT (MWT0-MWT6) measured in each 7 instances for every person (ID). I also have multiple predictors which I will add in the model later on to see whether they have an effect on the outcome over time (I did not include the predictors in the sample). For this, I wish to perform an HLM Model. I performed a HLM with YEARS and an other one with YEARS^2 using PROC MIXED to compare wich model fits my data best. Here are some example of the PROC MIXED I ran for now: Proc Mixed METHOD=ML covtest noclprint;
Class ID;
ID ID YEARS MWT;
Model MWT = YEARS /S DDFM = KR /*OUTP = PMWT (keep = ID YEARS MWT PRED) --> RUN LATER*/;
Random Int YEARS /subject = ID G TYPE = UN;
RUN;
YEARS2=YEARS*YEARS;
Proc Mixed covtest noclprint IC;
ID ID MWT YEARS
Class ID;
Model MWT = YEARS YEARS2/S DDFM = KR NOTEST;
Random Int YEARS YEARS2/subject = ID G TYPE = UN;
RUN; However, I expect my data to follow an exponential curve given the outcome will gradually increase overtime and reach a plateau (established from clinical experience). Hence, I would like to fit an exponential growth curve which I think I have to run using PROC NLMIXED or %NLINMIX. Unfortunately, I can't figure out how to fit my data with PROC NLMIXED in order to do an exponnential equation which I suppose should look like that: MWTij = µ0i e^(µ1i * YEARSij) + εij Here is a sample of my data: data work.MWTDATA;
infile datalines dsd truncover;
input ID:BEST12. VISIT:32. MONTH:32. YEARS:32. MWT:32.;
format ID BEST12.;
datalines4;
9000099,1,,0,15.12
9000099,2,,1.01,15.34
9000099,3,,2.09,14.75
9000099,4,,3.03,15.55
9000099,5,,4.06,15.51
9000099,6,,6.01,15
9000099,7,,7.88,15.87
9000622,1,,0,13.75
9000622,2,,1.01,12.65
9000622,3,,,
9000622,4,,,
9000622,5,,,
9000622,6,,,
9000622,7,,,
9000798,1,,0,18.47
9000798,2,,1.15,16.31
9000798,3,,2.3,16.73
9000798,4,,3.2,17.13
9000798,5,,4.12,16.09
9000798,6,,5.96,17.59
9000798,7,,8.02,18.16
9002116,1,,0,16.32
9002116,2,,1.06,14.12
9002116,3,,2.07,19.41
9002116,4,,2.99,22.01
9002116,5,,3.99,18.01
9002116,6,,6.02,16.6
9002116,7,,8.01,19.84
9003380,1,,0,13.26
9003380,2,,1.02,12.91
9003380,3,,2.04,12.54
9003380,4,,3.05,14.31
9003380,5,,4.05,13.53
9003380,6,,5.95,14.61
9003380,7,,7.84,15.65
9003406,1,,0,18.8
9003406,2,,1.36,16.78
9003406,3,,1.93,19.35
9003406,4,,3.22,17.18
9003406,5,,4.01,19.03
9003406,6,,5.98,16.94
9003406,7,,7.84,19.79
9004184,1,,0,28.52
9004184,2,,,
9004184,3,,,
9004184,4,,,
9004184,5,,,
9004184,6,,,
9004184,7,,,
9004905,1,,0,17.63
9004905,2,,1.33,18.39
9004905,3,,1.94,19.57
9004905,4,,2.94,19.81
9004905,5,,3.97,18.93
9004905,6,,5.99,14.93
9004905,7,,8.02,20.69
9005132,1,,0,16.56
9005132,2,,1.01,16.78
9005132,3,,2,15.37
9005132,4,,,
9005132,5,,,
9005132,6,,,
9005132,7,,,
9005656,1,,0,15.29
9005656,2,,1.45,14.15
9005656,3,,,
9005656,4,,,
9005656,5,,4.2,
9005656,6,,,
9005656,7,,,
9007827,1,,0,17.53
9007827,2,,1.2,16.54
9007827,3,,1.95,15.47
9007827,4,,2.95,15.89
9007827,5,,3.91,15.72
9007827,6,,6.08,17.93
9007827,7,,7.96,19.62
9008934,1,,0,13.5
9008934,2,,1.12,12.81
9008934,3,,2.13,14.69
9008934,4,,3.34,13
9008934,5,,4.15,14.11
9008934,6,,5.99,14.03
9008934,7,,8.02,13.32
9009623,1,,0,18.82
9009623,2,,0.95,17.29
9009623,3,,,
9009623,4,,,
9009623,5,,,
9009623,6,,,
9009623,7,,,
9011918,1,,0,14.82
9011918,2,,1.09,14.81
9011918,3,,,
9011918,4,,,
9011918,5,,,
9011918,6,,,
9011918,7,,,
9013161,1,,0,17.82
9013161,2,,1.42,
;;;; I figured I'd ask for help since this might not be so hard for some of you expert:) I am using SAS 9.4 for your reference! Thank You!
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