`R/EmpiricalCalibrationUsingAsymptotics.R`

`computeTraditionalP.Rd`

`computeTraditionalP`

computes the traditional two-sided p-value based on the log of the
relative risk and the standard error of the log of the relative risk.

`computeTraditionalP(logRr, seLogRr, twoSided = TRUE, upper = TRUE)`

- logRr
A numeric vector of one or more effect estimates on the log scale

- seLogRr
The standard error of the log of the effect estimates. Hint: often the standard error = (log(<lower bound 95 percent confidence interval>) - log(<effect estimate>))/qnorm(0.025)

- twoSided
Compute two-sided (TRUE) or one-sided (FALSE) p-value?

- upper
If one-sided: compute p-value for upper (TRUE) or lower (FALSE) bound?

The (traditional) p-value.

```
data(sccs)
positive <- sccs[sccs$groundTruth == 1, ]
computeTraditionalP(positive$logRr, positive$seLogRr)
#> [1] 0
```