Hi, Steve, I am sorry to bother you. The more I think, the more question that I have. I will make a summary about the total information that I have, and could I ask you a few questions based on it? The different groups are measured on each subject, for example: I want to measure each person's weight based on the position(lie, squat, stand), hand gesture(up, down, straight), location (1,2,3,4): the original dataset are like follows: Person position hand location1 location2 location3 location4
1 lie down 63 61 64 62
1 lie up 57 59 58 55
1 squat down 52 57 55 54
1 squat up 23 56 55 53
2 lie down 63 61 64 62
2 lie up 57 59 58 55
2 squat down 52 57 55 54
2 squat up 23 56 55 53 If I want to test the mean difference among all those groups, I should use repeated ANOVA since all those groups are nested within each person. However, if I want to test the assumptions: normality, homogeneity, and sphericity. I think only PROC GLM allows me to conduct sphericity test. So I could put four weights as dependent variables, and treat person, position, and hand as between-subject effect, and location as within-subject effect as following code: PROC GLM;
CLASS person position hand ;
MODEL location1 location2 location3 location4 = person|position|hand / nouni; REPEATED weight 4 / PRINTE ;
RUN ; However, the independence assumption is clearly violated because each value was measured within each person. In this case, do you think should I still can use PROC GLM, or I should use the PROC GLIMMIX by treating person as random effect like the post said (I will convert it to long format)? But if I use PROC GLIMMIX, I can't test the sphericity, and the homogeneity is violated. And if I use PROC GLM, the independence assumption is violated. What should I do about it? Sorry for the long question, but I am really struggling about this dataset. Thank you so much!
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