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The Wald test is a method to test whether explanatory variables influence outcomes. In the cases of Vol. 15 and Vol. 16, it is possible to investigate whether prescription drugs and smoking have a survival effect in the population using the Wald test.
[Table 1] Wald test results for past cases
P-value < 0.05 is significant, and p-value ≥ 0.05 is non-significant.
P-value ≥ 0.05 indicates no difference between prescription drugs and placebos in reducing mortality. In addition, the presence or absence of smoking demonstrated a p-value ≥ 0.05, therefore, it can be concluded that there was no difference between status of smoking in reducing the mortality rate.
[Table 2] Hazard ratio and confidence interval (95% CI)
In Vol. 16, the 95% CI for the prescription drug was from 0.071 to 2.116, which includes 1, thus, product A was not effective in prolonging life compared to a placebo. Similarly, the 95% CI for smoking status was also from 0.087 and 2.654, again including 1, therefore, implying that, as compared to smoking, non-smoking did not reduce mortality.
Thus, the interpretations of the Wald test and the 95% CI of the hazard ratio are the same.
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