Skip to contents

Binomial confidence intervals

binom_ci.Rd

[Stable]

Wrapper for binom::binom.confint

Usage

binom_ci(x, conf.level = 0.95, methods = "wilson", ...)

Arguments

x

vector of type integer (0/1) or logical (TRUE/FALSE)

conf.level

confidence level (between 0 and 1). Default is 0.95.

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 or "all". Default is "wilson".

...

Additional arguments to be passed to binom::binom.bayes

Value

data.frame with with mean (mean), and bounds of confidence interval (lower, upper)

Returns a data frame with the following columns:

  • method - method(s) selected

  • x - number of successes in the binomial experiment

  • n - number of independent trials in the binomial experiment

  • mean - success proportion mean

  • lower - success proportion lower bound

  • upper - success proportion upper bound

Details

See binom::binom.confint for method details

Examples


x <- c(rep(0, 500), rep(1, 500))
binom_ci(x, conf.level = .90, methods = 'all')
#>           method   x    n mean     lower     upper
#> 1  agresti-coull 500 1000  0.5 0.4740277 0.5259723
#> 2     asymptotic 500 1000  0.5 0.4739926 0.5260074
#> 3          bayes 500 1000  0.5 0.4740167 0.5259833
#> 4        cloglog 500 1000  0.5 0.4737084 0.5256940
#> 5          exact 500 1000  0.5 0.4735177 0.5264823
#> 6          logit 500 1000  0.5 0.4740160 0.5259840
#> 7         probit 500 1000  0.5 0.4740110 0.5259890
#> 8        profile 500 1000  0.5 0.4740102 0.5259898
#> 9            lrt 500 1000  0.5 0.4740164 0.5259836
#> 10     prop.test 500 1000  0.5 0.4690696 0.5309304
#> 11        wilson 500 1000  0.5 0.4740277 0.5259723