binom.conf.int {epitools} | R Documentation |
Confidence intervals for binomial counts or proportions
Description
Calculates confidence intervals for binomial counts or proportions
Usage
binom.exact(x, n, conf.level = 0.95)
binom.wilson(x, n, conf.level = 0.95)
binom.approx(x, n, conf.level = 0.95)
Arguments
x |
number of successes in n trials, can be a vector |
n |
number of Bernoulli trials, can be a vector |
conf.level |
confidence level (default = 0.95), can be a vector |
Details
The function, binom.exact
, calculates exact confidence intervals
for binomial counts or proportions. This function uses R's
binom.test
function; however, the arguments to this function
can be numeric vectors of any length.
The function, binom.wilson
, calculates confidence intervals for
binomial counts or proportions using Wilson's formula which
approximate the exact method. The arguments to this function
can be numeric vectors of any length (Rothman).
The function, binom.approx
, calculates confidence intervals for
binomial counts or proportions using a normal approximation to the
binomial distribution. The arguments to this function can be numeric
vectors of any length.
Value
This function returns a n x 6 matrix with the following colnames:
x |
number of successes in n trials |
n |
number of Bernoulli trials |
prop |
proportion = x/n |
lower |
lower confidence interval limit |
upper |
upper confidence interval limit |
conf.level |
confidence level |
Author(s)
Tomas Aragon, aragon@berkeley.edu, http://www.phdata.science
References
Tomas Aragon, et al. Applied Epidemiology Using R. Available at http://www.phdata.science
Kenneth Rothman (2002), Epidemiology: An Introduction, Oxford University Press, 1st Edition.
See Also
Examples
binom.exact(1:10, seq(10, 100, 10))
binom.wilson(1:10, seq(10, 100, 10))
binom.approx(1:10, seq(10, 100, 10))