I'm working on bankruptcy prediction models using logit regression with unbalanced data between the size of bankrupt and healthy firms (as mentioned in the table below ) , i found Corrected classification rate around 95% but this rate ignore low rate of prediction of bankrupt firms ( this due to the assumption of equal cost of miss-classification for both classes). Please how i can give a higher rate (cost) to the false negative than the false positive ? to minimize the average cost of miss-classification. Thank you

. estat classification

Logistic model for dep

estat classification

Logistic model for dep

-------- True --------

Classified | D ~D | Total

-----------+--------------------------+-----------

+ | 2 8 | 10

- | 596 99342 | 99938

-----------+--------------------------+-----------

Total | 598 99350 | 99948

Classified + if predicted Pr(D) >= .5

True D defined as dep != 0

--------------------------------------------------

Sensitivity Pr( +| D) 0.33%

Specificity Pr( -|~D) 99.99%

Positive predictive value Pr( D| +) 20.00%

Negative predictive value Pr(~D| -) 99.40%

--------------------------------------------------

False + rate for true ~D Pr( +|~D) 0.01%

False - rate for true D Pr( -| D) 99.67%

False + rate for classified + Pr(~D| +) 80.00%

False - rate for classified - Pr( D| -) 0.60%

--------------------------------------------------

Correctly classified 99.40%

. estat classification

Logistic model for dep

estat classification

Logistic model for dep

-------- True --------

Classified | D ~D | Total

-----------+--------------------------+-----------

+ | 2 8 | 10

- | 596 99342 | 99938

-----------+--------------------------+-----------

Total | 598 99350 | 99948

Classified + if predicted Pr(D) >= .5

True D defined as dep != 0

--------------------------------------------------

Sensitivity Pr( +| D) 0.33%

Specificity Pr( -|~D) 99.99%

Positive predictive value Pr( D| +) 20.00%

Negative predictive value Pr(~D| -) 99.40%

--------------------------------------------------

False + rate for true ~D Pr( +|~D) 0.01%

False - rate for true D Pr( -| D) 99.67%

False + rate for classified + Pr(~D| +) 80.00%

False - rate for classified - Pr( D| -) 0.60%

--------------------------------------------------

Correctly classified 99.40%