Calculates the Clopper-Pearson interval by calling stats::binom.test()
.
Also referred to as the exact
method.
Usage
ci_prop_clopper_pearson(x, conf.level = 0.95, data = NULL)
Arguments
- x
(binary
/numeric
/logical
)
vector of a binary values, i.e. a logical vector, or numeric with values c(0, 1)
- conf.level
(scalar numeric
)
a scalar in (0,1) indicating the confidence level. Default is 0.95
- data
(data.frame
)
Optional data frame containing the variables specified in x
and by
.
Details
$$
\left( \frac{k}{n} \pm z_{\alpha/2} \sqrt{\frac{\frac{k}{n}(1-\frac{k}{n})}{n} +
\frac{z^2_{\alpha/2}}{4n^2}} \right)
/ \left( 1 + \frac{z^2_{\alpha/2}}{n} \right)$$