BookmarkSubscribeRSS Feed
Ruhi
Obsidian | Level 7

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. 

Torsion pic.png

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

2 REPLIES 2
PGStats
Opal | Level 21

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?

PG
Ruhi
Obsidian | Level 7

Here is the distribution after subtracting the means from each condition. It is still multi-modal. Histogram2.png

sas-innovate-wordmark-2025-midnight.png

Register Today!

Join us for SAS Innovate 2025, our biggest and most exciting global event of the year, in Orlando, FL, from May 6-9. Sign up by March 14 for just $795.


Register now!

How to Concatenate Values

Learn how use the CAT functions in SAS to join values from multiple variables into a single value.

Find more tutorials on the SAS Users YouTube channel.

SAS Training: Just a Click Away

 Ready to level-up your skills? Choose your own adventure.

Browse our catalog!

Discussion stats
  • 2 replies
  • 582 views
  • 0 likes
  • 2 in conversation