Published on *OpenMx* (http://openmx.psyc.virginia.edu)

By *K Ram*

Created *08/21/2012 - 02:05*

Tue, 08/21/2012 - 02:05 — K Ram [1]

Hello

Some of the variables in my dataset do not satisfy the assumption that the data should be normally distributed. So I am unable to rationally run parametric SEM analyses.

I have attempted to transform the data to approximate a normal distribution using cumulative distribution functions, log10 and square root transformations, but with no success. These transformations slightly shifts the skewness or squeezes the data together, however the data remains immune to normality.

1. What steps can be taken when the normality assumptions cannot be met?

2. Are there any openMx scripts designed for non-normal data?

3. Any other suggestions??

Many thanks

**Links:**

[1] http://openmx.psyc.virginia.edu/users/k-ram

[2] http://openmx.psyc.virginia.edu/thread/1555

[3] http://openmx.psyc.virginia.edu/thread/1491

[4] http://openmx.psyc.virginia.edu/forums/opensem-forums/behavioral-genetics-models