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significant when the values of τ vary. For example, “Size” in both scenarios.

Furthermore, parameter estimates vary when the correlation between the depen-
dent censoring and events changes. In some cases, the estimates vary slightly. For
example, “Age” from the second scenario. The estimates may vary quite a bit. For
instance, “Profit” in the first scenario. Detailed results are shown below.

• Tests 3, 4, 5 and 6

Tables 4.3 - 4.12 present parameter estimates and related standard errors and 95
percent confidence intervals for both bankruptcy and acquisition scenarios. Figures
4.1 - 4.10 illustrate such data graphically. In those figures, “Beta” represents the first
scenario and “Betac” represents the second. Р-values are calculated based on the fact
that the following statistic (-g∙‰)² follows the χ² distribution.

Figure 4.11 shows the cumulative hazard curve of bankruptcy obtained using the
proposed method and its 95 percent confidence interval. It will be further discussed
in Chapter 5.

Table 4.3: Results for Covariate 1 - Growth for Bankruptcies

	τ = —0.5	τ = 0	τ = 0.2	τ = 0.5	τ = 0.8
Parameters	-0.870	0.116	0.204	0.169	0.166
SE of Est	1.127	0.440	0.232	0.247	0.208
Upper Bound	1.338	0.978	0.658	0.654	0.575
Lower Bound	-3.079	-0.746	-0.251	-0.315	-0.242

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