add4ci: Agresti-Coull add-4 CI for a binomial proportion

In PropCIs: Various Confidence Interval Methods for Proportions

Description

Agresti-Coull add-4 CI for a binomial proportion, based on adding 2 successes and 2 failures before computing the Wald CI. The CI is truncated, when it overshoots the boundary

Usage

add4ci(x, n, conf.level)

Arguments

x	number of successes
n	number of trials
conf.level	confidence coefficient

Value

A list with class '"htest"' containing the following components:

conf.int	The confidence intervall for the proportion
estimate	The estimator for the proportion

References

Agresti, A., Coull, B. (1998) Approximate is better than exact for interval estimation of binomial proportions. The American Statistician 52, 119–126.

Agresti, A., Caffo, B.(2000) Simple and effective confidence intervals for proportions and difference of proportions result from adding two successes and two failures. The American Statistician 54 (4), 280–288.

Examples

add4ci(x = 15, n = 112, conf.level = 0.95)

Example output

data:  

95 percent confidence interval:
 0.08219363 0.21090982
sample estimates:
[1] 0.1465517

PropCIs documentation built on May 2, 2019, 5:49 a.m.