CALCULATION OF P VALUES
Although the investigator is better off relying on estimation rather than tests of statistical significance for inference, for completeness, we give the basic formulas from which traditional P values can be derived that test the null hypothesis that exposure is not related to disease.
Risk Data
For risk data, we use the following expansion of the notation used earlier in the chapter:
Exposed 
Unexposed 
Total 

Cases 
a 
b 
^{M}1 
Noncases 
c 
d 
^{M}0 
People at risk 
^{N}1 
^{N}0 
T 
The P value testing the null hypothesis that exposure is not related to disease can be obtained from the following equation for ?
For the data in Table 91, Equation 97 gives x as follows:
The P value that corresponds to this x statistic must be obtained from tables of the standard normal distribution (see Appendix). For a x of 4.78 (minus sign indicates only that the exposed group had a lower risk than the unexposed group), the P value is very small (roughly 0.0000009). The Appendix tabulates values of X only from 3.99 to +3.99.
Incidence Rate Data
For incidence rate data, we use the following notation, which is an expanded version of the table we used earlier:
Exposed 
Unexposed 
Total 
Cases a 
b 
M 
Persontime PT_{1} 
^{PT}0 
T 
for which we can use the following equation to calculate
Applying this equation to the data of Table 92 gives the following result for ?
This x is so large in absolute value that the P value cannot be readily calculated. The P value corresponding to a x of 8.92 is much smaller than 1020, implying that the data are not readily consistent with a chance explanation.
CaseControl Data
For casecontrol data, we can apply Equation 97 to the data in Table 93.
From the appendix table, we see that this result corresponds to a P value of 0.00022.