Hi
I am stuck with analysis of a data which seems a mixture of two normals distributions.
Experimental design: So we gatherad data on pelvic torsion on subjects, under 5 diffrent conditions, 3 trials of each condition and each condition will generate 12 images, so 12 objective records for each person at each trial and condition level. A person's pelvis could have torsion in positive direction and others could just have it in negative direction, generating a bi-modal distribution shown below.
I want to model the mean torsion for each different condition. My resaerch into mixture models suggested that I could use proc FMM in SAS, but it cant handle correlated observations and random effects. As I have random trials and images with in each trial, I am not sure how should I analyse this data.
Any help is very much appreciated?
Thanks
What we are looking at is the distribution of the data (effect + error). What you need to model is the distribution of the errors. What does that distribution look like after you substract the mean for each condition?
Here is the distribution after subtracting the means from each condition. It is still multi-modal.
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