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Specialized on Data processing, Data management Implementation plan, Data Collection tools - electronic and paper base, Data cleaning specifications, Data extraction, Data transformation, Data load, Analytical Datasets, and Data analysis. BJ Data Tech Solutions teaches on design and developing Electronic Data Collection Tools using CSPro, and STATA commands for data manipulation. Setting up Data Management systems using modern data technologies such as Relational Databases, C#, PHP and Android.

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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Home / Data Cleaning / Data management / Data Processing / Comparing two probit models with clustered standard errors Comparing two probit models with clustered standard errors

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