Dear NMusers,

I have two questions regarding the statistical model when performing
external validation. I have a dataset and would like to validate a
published model with POSTHOC method i.e. $EST METHOD=0 POSTHOC MAXEVAL=0.

1. The model added etas in proportional way, i.e. Para = THETA * (1+ETA)
and this made the posthoc estimation fail due to the negative individual
parameter estimate in some subjects. I constrained it to be positive by
adding ABS function i.e. Para = THETA * ABS(1+ETA), and the estimation can
be successfully running. I was wondering if there is better workaround?

2. OMEGA value influences individual ETAs in POSTHOC estimation. Should we
assign $SIGMA with model value or lab (where external data was determined)
assay error value? If we use model value, it's understandable that $SIGMA
contains unexplained variability and thus it is a part of the model.
However, I may also understand it as that model value contains the
unexplained variability for original data (in which the model was created)
but not for external data. I'm a little confused about it. Can someone help
me out?

I would appreciate any response! Many thanks in advance!

Your sincerely,

Tingjie Guo

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