Information Matrix

In my previous blog I described a real case where so-called artificial intelligence (AI) would have struggled to spot data problems that a (suspicious) human could find.  But what if the input data are clean and reliable?

When fitting a mortality model, analysts are faced with the decision of which risk factors to include or exclude.  One way of doing this is to look for the improvement in an information criterion that balances the fit against the number of parameters.  The bigger the improvement in the information criterion, the more strongly the model with the smaller value is preferred.