Calculates the Jeffreys interval, an equal-tailed interval based on the non-informative Jeffreys prior for a binomial proportion.
ci_prop_jeffreys(x, conf.level = 0.95, data = NULL)An object containing the following components:
Number of responses
Total number
The point estimate of the proportion
Lower bound of the confidence interval
Upper bound of the confidence interval
The confidence level used
Type of method used
(binary/numeric/logical)
vector of a binary values, i.e. a logical vector, or numeric with values c(0, 1)
(scalar numeric)
a scalar in (0,1) indicating the confidence level. Default is 0.95
(data.frame)
Optional data frame containing the variables specified in x and by.
$$\left( \text{Beta}\left(\frac{k}{2} + \frac{1}{2}, \frac{n - k}{2} + \frac{1}{2}\right)_\alpha, \text{Beta}\left(\frac{k}{2} + \frac{1}{2}, \frac{n - k}{2} + \frac{1}{2}\right)_{1-\alpha} \right)$$