ci_p_clopper_pearson | R Documentation |
This function calculates the confidence interval for a proportion. It is vectorized, allowing users to evaluate it using either single values or vectors.
ci_p_clopper_pearson(x, n, conf.level = 0.95)
x |
A number or a vector with the number of successes. |
n |
A number or a vector with the number of trials. |
conf.level |
Confidence level for the returned confidence interval. By default, it is 0.95. |
The Clopper-Pearson interval is an exact confidence interval for the
Binomial proportion p
.
The limits of the interval are derived based on the Beta distribution.
For the special cases where x=0
or x=n
, the limits are
calculated directly.
The mathematical definitions are as follows:
- If x=0
, the lower limit is 0
, and the upper limit is 1 - (\alpha / 2)^{1/n}
.
- If x=n
, the lower limit is (\alpha / 2)^{1/n}
, and the
upper limit is 1
.
Otherwise, the limits are given by:
\text{Lower Limit}=B_{1-\alpha/2, x, n-x+1}
\text{Upper Limit}=B_{\alpha/2, x+1, n-x}
where B_{\omega, a, b}
is the 100\%(1-\omega)
percentile of the Beta distribution with parameters
a
and b
.
Due to the relationship between Beta and F distributions, the limits can be written as:
\text{Lower Limit}=\frac{1}{1+\frac{n-x+1}{x}F_{\alpha/2, \, 2(n-x+1), \, 2x}}
\text{Upper Limit}=\frac{\frac{x+1}{n-x} F_{\alpha/2, \, 2(x+1), \, 2(n-x)}}{1+\frac{x+1}{n-x} F_{\alpha/2, \, 2(x+1), \, 2(n-x)}}
where F_{\omega, a, b}
is the 100\%(1-\omega)
percentile of the F distribution with parameters
a
and b
.
A vector with the lower and upper limits.
Omar David Mercado Turizo, omercado@unal.edu.co
Clopper, C. J., & Pearson, E. S. (1934). The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika, 26(4), 404-413.
ci_p.
ci_p_clopper_pearson(x=15, n=50, conf.level=0.95)
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