Hi,
I am trying to detect and identify bivariate outliers in a dataset using OpenMx, in order to see whether specific outliers have significant contribution. Preferrably the output would be like that of %p in old Mx.
(i.e. 8 columns with:
1) -2lnL,
2) Mahalanobis,
3) estimated Z,
4) number of observations in data set,
5) number of data points in vector,
6) optimization details,
7) whether or not likelihood was calculable, and
8) model number if there are multiple models)
I have already tried using the vector=TRUE argument in FIMLobjective (as suggested in https://openmx.ssri.psu.edu/thread/584), however ID number is not included and I am unsure whether the output is in the same order as in the data file.
Any help would be appreciated, thanks.