Calculates the Jeffreys interval, an equal-tailed interval based on the
non-informative Jeffreys prior for a binomial proportion.
Usage
ci_prop_jeffreys(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.
Value
An object containing the following components:
- n
Number of responses
- N
Total number
- estimate
The point estimate of the proportion
- conf.low
Lower bound of the confidence interval
- conf.high
Upper bound of the confidence interval
- conf.level
The confidence level used
- method
Type of method used
Details
$$\left( \text{Beta}\left(\frac{k}{2} + \frac{1}{2}, \frac{n - k}{2} + \frac{1}{2}\right)_\alpha,
\text{Beta}\left(\frac{k}{2} + \frac{1}{2}, \frac{n - k}{2} + \frac{1}{2}\right)_{1-\alpha} \right)$$