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Comparing two probit models with clustered standard errors
Comparing two probit models with clustered standard errors

Hey everyone,

I would like to compare two probit models (that are nested) to see whether the addition of further variables improves the model. As I need clustered standard errors, it is not possible to use a likelihood ratio test. Which other possibilites do I have? Is it appropriate to compare the AIC/BIC or do another test?

Looking forward to some advice. Thanks! :-)

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