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Count R2. Since the conventional R2 value may not be appropriate for linear probability models, one suggested alternative is the count R2, which is defined as:
Since in LPM the dependent variable takes a value of 1 or 0, if the predicted probability is greater than 0.5, we classify that as 1, but if the predicted probability is less than 0.5, we classify that as 0. We then count the number of correct predictions and compute the count R2 from the formula given above.
Find the count R2 for the model (6.32). How does it compare with the conventional R2 given in that equation? |
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