`R/ConfidenceIntervalCalibration.R`

`computeTraditionalCi.Rd`

`computeTraditionalCi`

computes the traditional confidence interval based on the log of the
relative risk and the standard error of the log of the relative risk.

`computeTraditionalCi(logRr, seLogRr, ciWidth = 0.95)`

- 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)

- ciWidth
The width of the confidence interval. Typically this would be .95, for the 95 percent confidence interval.

The point estimate and confidence interval

```
data(sccs)
positive <- sccs[sccs$groundTruth == 1, ]
computeTraditionalCi(positive$logRr, positive$seLogRr)
#> rr lb ub
#> 1 2.080532 1.800637 2.403934
```