binom.confint {binom}R Documentation

Binomial confidence intervals


Uses eight different methods to obtain a confidence interval on the binomial probability.


binom.confint(x, n, conf.level = 0.95, methods = "all", ...)



Vector of number of successes in the binomial experiment.


Vector of number of independent trials in the binomial experiment.


The level of confidence to be used in the confidence interval.


Which method to use to construct the interval. Any combination of c("exact", "ac", "asymptotic", "wilson", "prop.test", "bayes", "logit", "cloglog", "probit") is allowed. Default is "all".


Additional arguments to be passed to binom.bayes.


Nine methods are allowed for constructing the confidence interval(s):

By default all eight are estimated for each value of x and/or n. For the "logit", "cloglog", "probit", and "profile" methods, the cases where x == 0 or x == n are treated separately. Specifically, the lower bound is replaced by (alpha/2)^n and the upper bound is replaced by (1-alpha/2)^n.


A data.frame containing the observed proportions and the lower and upper bounds of the confidence interval for all the methods in "methods".


Sundar Dorai-Raj (


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

R.G. Newcombe, Logit confidence intervals and the inverse sinh transformation (2001), American Statistician, 55:200-202.

L.D. Brown, T.T. Cai and A. DasGupta (2001), Interval estimation for a binomial proportion (with discussion), Statistical Science, 16:101-133.

Gelman, A., Carlin, J. B., Stern, H. S., and Rubin, D. B. (1997) Bayesian Data Analysis, London, U.K.: Chapman and Hall.

See Also

binom.bayes, binom.logit, binom.probit, binom.cloglog, binom.coverage, prop.test, binom.test for comparison to method "exact"


binom.confint(x = c(2, 4), n = 100, tol = 1e-8)

[Package binom version 1.1-1 Index]