Financial Ratios and Discriminant Analysis
power on observations other than those used to establish the parameters of
the model. Therefore, any search bias does not appear significant.
TABLE 3
ACCURACY OF CLASSIFYING A SECONDARY SAMPLE
Per cent of Correct Value
Replication Classifications of t
1 91.2 4.8*
2 91.2 4.8*
3 97.0 S.5*
4 97.0 4.S*
5 91.2 4.8*
Average 93.5 5.1*
Total number of observations per replication 34
* Significant at the .001 level.
proportion correct — .5
V-.5(1-.5)
(4) Secondary Sample of Bankrupt Firms. In order to test the model rigorously
for both bankrupt and non-bankrupt firms two new samples are introduced.
The first contains a new sample of twenty-five bankrupt firms whose
asset-size range is the same as that of the initial bankrupt group. Using the
parameters established in the discriminant model to classify firms in this
secondary sample, the predictive accuracy for this sample as of one statement
prior to bankruptcy is:
Bankrupt
Group
(Actual)
Type I
(total)
Number
Correct
24
Bankrupt
24
Per cent
Correct
96
Predicted
Per cent
Error
4
Non-Bankrupt
1
n
25
The results here are surprising in that one would not usually expect a secondary
sample's results to be superior to the initial discriminant sample (96 per
cent vs. 94 per cent). Two possible reasons are that the upward bias normally
present in the initial sample tests is not manifested in this investigation, and/or
the model, as stated before, is something less than optimal.
(S) Secondary Sample of Non-Bankrupt Firms. Up to this point the sample
companies were chosen either by their bankruptcy status (Group 1) or by
their similarity to Group 1 in all aspects except their economic well-being. But
what of the many firms which suffer temporary profitability difficulties, but
in actuality do not become bankrupt. A bankruptcy classification of a firm
from this group is an example of a Type II error. An exceptionally rigorous