Hi guys, I'm working on this project analyzing if different exercises (ie squats, shoulder press....) can explain spine angle and loading with different lift combinations...symmetry (symmetric & asymmetric) and loads (heavy and light). 20 subjects are to perform 2 different types of lifts (symmetric and asymetric) with 2 loads (heavy weight and light weight). Spine angle (bend, twist, flex) and spine load (comp, ap, ml) are measured for each type/load (symmetric/heavy, symmetric/light, asym/heavy, asym/light). 7 exercises (dsqt, hstp, ilng, shld, aslr, pshp, rtry) were also performed for each type/load, the subjects report the feeling (scale from 1 to 4, 1 is painful and 4 is comfortable) they experienced while doing each of these exercises. I would like to see which (if any) of the 7 exercises explains the spine angle and load. Also comparing the results between symmetric/asymmetric. I'm not sure how exactly to do this with either PROC MIXED or PROC GLM. Here is my attempt at it, but I'm sure it's not right. Can someone give me a pointer? data wide; input subject age height mass group symmetry$ load$ bend twist flex comp ap ml dsqt hstp ilng shld aslr pshp rtry; datalines; s01 28 1.81 77.1 hi asym heavy 2.3 1.1 88 9.2 .32 .12 2 2 3 3 3 2 2 s02 34 1.57 67.1 lo asym heavy 4.3 2.1 98 4.2 .36 .22 3 2 4 3 2 4 2 . . s01 28 1.81 77.1 hi asym light 2.3 1.1 88 9.2 .32 .12 2 2 3 3 3 2 2 s02 34 1.57 67.1 lo asym light 4.3 2.1 98 4.2 .36 .22 3 2 4 3 2 4 2 . . s01 28 1.81 77.1 hi sym heavy 8.3 7.1 58 2.2 .92 .13 1 2 1 3 4 2 4 s02 34 1.57 67.1 lo sym heavy 4.6 2.8 91 4.4 .96 .72 3 1 4 2 2 4 4 . . s01 28 1.81 77.1 hi sym light 3.3 1.9 68 3.2 .32 .12 2 2 1 1 3 4 2 s02 34 1.57 67.1 lo sym light 2.3 5.1 28 4.2 .36 .22 3 2 1 2 2 1 2 . . ; data long; length var$12; length var2$12; set data wide; response=bend; var='bend';output; response=twist; var='twist';output; response=flex; var='flex';output; response=comp; var='comp';output; response=ap; var='ap';output; response=ml; var='ml';output; exercise=dsqt; var2='dsqt'; output; exercise=hstp; var2='hstp'; output; exercise=ilng; var2='ilng'; output; exercise=shld; var2='shld';output exercise=aslr; var2='aslr';output; exercise=pshp; var2='pshp';output; exercise=rtry; var2='rtry';output; drop bend twist flex comp ap ml dsqt hstp ilng shld aslr pshp try; proc mixed data=long; class subject age height mass group symmetry load var var2; model response = age|height|mass|group|symmetry|load|var|var2|exercise; repeated var var2 / type=un@ar(1) subject=subject; run; thanks. ming
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