A similar classification rule can be used by the MDA, logit, or probit scores (probabilities), but the number of misclassifications with NPDM will be always less than, or equal to, the number of misclassifications obtained by the MDA or logit for an estimation sample.
They are applicable for MDA, NPDM, LPM, logit, probit, lomit, etc.
The separation indices IS(b) improve slightly when the NPDM models are applied.
However, a substantial computational burden is involved in calculating the NPDM and qualitative response models with so many independent variables.
The NPDM correctly classifies a few more firms for the three base years, but the improvement is insignificant.
Both the NPDM and MDA provide similar results two years prior to insolvency, but the NPDM slightly outperforms MDA one and three years prior to insolvency.
The Lomit or Burrit and the NPDM do not assume that the scores (given to the firms) are symmetrically distributed, and therefore they may better fit the data than MDA.
In addition, the NPDM outperforms both the logit and the MDA model in terms of prediction or validation results.