Determines the expected length for a binomial confidence interval.
1  binom.length(p, n, conf.level = 0.95, method = "all", ...)

p 
The (true) probability of success in a 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. 
method 
Either a character string to be passed to

... 
Additional parameters to be passed to

Derivations are based on the results given in the references. Methods
whose length probabilities are consistently closer to 0.95 are more
desireable. Thus, Wilson's, logit, and cloglog appear to be good for
this sample size, while Jeffreys, asymptotic, and prop.test are
poor. Jeffreys is a variation of Bayes using prior shape parameters of
0.5 and having equal probabilities in the tail. The Jeffreys'
equaltailed interval was created using binom.bayes using (0.5,0.5) as
the prior shape parameters and type = "central"
.
A data.frame
containing the "method"
used, "n"
, "p"
,
and the average length, L(p,n)
.
Sundar DoraiRaj (sdorairaj@gmail.com)
L.D. Brown, T.T. Cai and A. DasGupta (2001), Interval estimation for a binomial proportion (with discussion), Statistical Science, 16:101133.
L.D. Brown, T.T. Cai and A. DasGupta (2002), Confidence Intervals for a Binomial Proportion and Asymptotic Expansions, Annals of Statistics, 30:160201.
binom.confint
, binom.coverage
1  binom.length(p = 0.5, n = 50)

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