| binom.confint {binom} | R Documentation |
Uses eight different methods to obtain a confidence interval on the binomial probability.
binom.confint(x, n, conf.level = 0.95, methods = "all", ...)
x |
Vector of number of successes in the binomial experiment. |
n |
Vector of number of independent trials in the binomial experiment. |
conf.level |
The level of confidence to be used in the confidence interval. |
methods |
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):
exactbinom.test.asymptoticagresti-coullwilsonprop.testprop.test(x = x, n = n,
conf.level = conf.level)$conf.int.bayesbinom.bayes.logitbinom.logit.cloglogbinom.cloglog.probitbinom.probit.profilebinom.profile.
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 (sdorairaj@gmail.com)
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.
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)