# frequentist: Frequentist inference about the relative risk In brr: Bayesian Inference on the Ratio of Two Poisson Rates

## Description

Frequentist confidence intervals about the relative risk: binomial interval (`rr_interval_binomial`) and Sahai and Khurshid confidence interval (`rr_interval_SK`)

## Usage

 ```1 2 3 4 5``` ```rr_interval_SK(x, y, S, T, conf = 0.95) rr_interval_binomial(x, y, S, T, conf = 0.95) rr_intervals(x, y, S, T, conf = 0.95) ```

## Arguments

 `x,y` Observed counts `S,T` sample sizes `conf` confidence level

## Details

The binomial interval (`rr_interval_binomial`) is the classical confidence interval obtained by conditionning on the sum `x+y` of the two counts. The same interval is implemented in the `rateratio.test` package. The Sahai and Khurshid interval (`rr_interval_SK`) is an unconditional confidence interval. See the reference for more details and a study of its performance.

## Value

`rr_interval_binomial` and `rr_interval_SK` return the bounds of the confidence interval in a vector, `rr_intervals` returns a list with the two confidence intervals

## References

S. Laurent, C. Legrand: A Bayesian framework for the ratio of two Poisson rates in the context of vaccine efficacy trials. ESAIM, Probability & Statistics 16 (2012), 375–398.

## Examples

 ```1 2 3``` ```x <- 3; y <- 10; S <- 100; T <- 100 rr_intervals(x, y, S, T) brr_intervals(x, y, S, T) ```

brr documentation built on May 29, 2017, 3:10 p.m.