Binomial confidence intervals using the logit parameterization

Uses the logistic (logit) parameterization on the observed proportion to construct confidence intervals.

binom.logit(x, n, conf.level = 0.95, ...)

Arguments

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.
...: ignored

Details

For derivations see doc/binom.pdf.

Value

A data.frame containing the observed proportions and the lower and upper bounds of the confidence interval.

Author

Sundar Dorai-Raj (sdorairaj@gmail.com)

Examples

binom.logit(x = 0:10, n = 10)
#>    method  x  n mean      lower     upper
#> 1   logit  0 10  0.0 0.00000000 0.3084971
#> 2   logit  1 10  0.1 0.01388166 0.4672367
#> 3   logit  2 10  0.2 0.05041281 0.5407080
#> 4   logit  3 10  0.3 0.09976832 0.6236819
#> 5   logit  4 10  0.4 0.15834201 0.7025951
#> 6   logit  5 10  0.5 0.22450735 0.7754927
#> 7   logit  6 10  0.6 0.29740491 0.8416580
#> 8   logit  7 10  0.7 0.37631807 0.9002317
#> 9   logit  8 10  0.8 0.45929200 0.9495872
#> 10  logit  9 10  0.9 0.53276327 0.9861183
#> 11  logit 10 10  1.0 0.69150289 1.0000000