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I'm working on modeling and comparing data sets, and I need a good way to see if there is a significant difference between the data from the 2 models. An example of the models are here.

I initially thought of using the models to generate data, and to then run a t-test on the generated data to notice any significant differences. Another approach that was recommended was performing a chi squared goodness-of-fit test on generated data to see if the models are accurate.

Is there a better, more accurate or statistically "correct" method to compare these models?

P.S. For what it's worth, I'm using R to perform my analysis.

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