wilsonCI: Wilson (Agresti-Coull) CI for a Binomial Proportion

In abd: The Analysis of Biological Data

Description

Calculate the confidence interval for a "small sample" binomial proportion using the Agresti-Coull (1998) method. Useful for small samples where the Wald "large sample" normal test used by binom.test is not appropriate (when n is small or when p is close to 0 or 1).

Usage

wilsonCI(x, n, conf.level = 0.95)

Arguments

x	an integer number of successes
n	an integer number of trials
conf.level	the confidence level for interval estimation; defaults to 0.95

Value

Returns an object of type prop.ci, which includes:

x	the number of successes
n	the number of trials
conf.level	the confidence interval level
lower	the lower bound of the confidence interval
upper	the upper bound of the confidence interval
interval	the interval
estimate	the estimated proportion ((x+2)/(n+4))

Author(s)

Kevin M. Middleton ([e-mail])

References

Agresti, A. and B.A. Coull. 1998. Approximate is better than "exact" for interval estimation of binomial proportions. The American Statistician 52: 119-126. http://www.jstor.org/stable/2685469

See Also

binom.test

Examples

propCI(7, 50)
propCI(7, 50, conf.level = 0.99)
# should be very close to the score interval of prop.test
prop.test(7,50)

abd documentation built on May 2, 2019, 4:46 p.m.