Hello Shivam,

As your query doesn't address a particular model, I can only offer some generic suggestions.

How to defend a model:

1. Show that the proposed set of relationships is consistent with theory, prior research, or both. (This, before the analysis.)

2. Show that the proposed model adequately accounts for the observed relationships in your data set. (This, after the analysis.)

3. When there are competing theories for the phenomenon under investigation, compare the performance of your selected model to that of competing models. (This, after the analysis.)

Of course, you should check to see that there are no impossible relationships proposed in your model (for example, asserting that one's attitude (as a middle-aged adult) towards immigrants influences one's attitude (as an adolescent) towards immigrants), that you have sufficient indicator variables for any proposed latent variable, and so on.

Good luck with your work.

What did they (the panel members) say was wrong with the model in their opinion?

"Wrong" is very ambigious. It may be wrong from a theoretical standpoint, that you built a wrong model, which is not in accordance with your underlying theory. Wrong could also mean "bad fit", that you modeled it according to your theory, but the bad fit indicates that your data and theory do not fit very well. Or you did something technically wrong, so you specified something that should not be (e.g. items are on the wrong latent variable). Or wrong in the sense of "suboptimal", e.g. maximum likelihood estimators for ordinal items.

So please clarify!