it sounds like that covariate provides information for the parameter influenced 
by eta.
you have taken something that was unexplained population variation and 
explained part of it with the covariate.
this is usually a good thing.
if the covariate helps so much to predict the parameter that the eta becomes 
very small and as a result gets a high shrinkage then this can happen when 
there isnt much information left.
can you just do the regular hypothesis testing?
try removing the eta i.e. (0 FIXED) , reestimate and compare AIC? and whatever 
other metrics you might use.
warm regards
Douglas

________________________________
Van: [email protected] [mailto:[email protected]] Namens 
Xinting Wang
Verzonden: January 22, 2015 8:27 AM
Aan: [email protected]
Onderwerp: [NMusers] Covariate lead to increase in Eta shrinkage

Dear all,

I have a model that I am currently working on that is going through covariate 
selection. There's one particular parameter, whose ETA-shrinkage before adding 
any covariate was 25%. However, after adding a covariate successfully, the 
ETA-shrinkage was increased to almost 80%. While the model parameter estimation 
in this final model is reasonable, and there's no warnings or errors in the 
output file, the increase in the ETA-shrinkage basically means that the 
individual estimation falls back to population estimation. Under such a 
circumstance, how should I decide if it's reasonable to keep this parameter? 
Thank you.

Best Regards

--
Xinting
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