# binCI: Confidence intervals for binomial probability of success. In FSA: Simple Fisheries Stock Assessment Methods

## Description

Uses one of three methods to compute a confidence interval for the probability of success (p) in a binomial distribution.

## Usage

 ```1 2 3 4 5 6 7``` ```binCI( x, n, conf.level = 0.95, type = c("wilson", "exact", "asymptotic"), verbose = FALSE ) ```

## Arguments

 `x` A single or vector of numbers that contains the number of observed successes. `n` A single or vector of numbers that contains the sample size. `conf.level` A single number that indicates the level of confidence (default is `0.95`). `type` A string that identifies the type of method to use for the calculations. See details. `verbose` A logical that indicates whether `x`, `n`, and `x/n` should be included in the returned matrix (`=TRUE`) or not (`=FALSE`; DEFAULT).

## Details

This function will compute confidence interval for three possible methods chosen with the `type` argument.

 `type="wilson"` Wilson's (Journal of the American Statistical Association, 1927) confidence interval for a proportion. This is the score CI, based on inverting the asymptotic normal test using the null standard error. `type="exact"` Computes the Clopper/Pearson exact CI for a binomial success probability. `type="asymptotic"` This uses the normal distribution approximation.

Note that Agresti and Coull (2000) suggest that the Wilson interval is the preferred method and is, thus, the default `type`.

## Value

A #x2 matrix that contains the lower and upper confidence interval bounds as columns and, if `verbose=TRUE` `x`, `n`, and `x/n` .

## Author(s)

Derek H. Ogle, derek@derekogle.com, though this is largely based on `binom.exact`, `binom.wilson`, and `binom.approx` from the old epitools package.

## References

Agresti, A. and B.A. Coull. 1998. Approximate is better than “exact” for interval estimation of binomial proportions. American Statistician, 52:119-126.

## See Also

See `binom.test`; `binconf` in Hmisc; and functions in binom.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```## All types at once binCI(7,20) ## Individual types binCI(7,20,type="wilson") binCI(7,20,type="exact") binCI(7,20,type="asymptotic") binCI(7,20,type="asymptotic",verbose=TRUE) ## Multiple types binCI(7,20,type=c("exact","asymptotic")) binCI(7,20,type=c("exact","asymptotic"),verbose=TRUE) ## Use with multiple inputs binCI(c(7,10),c(20,30),type="wilson") binCI(c(7,10),c(20,30),type="wilson",verbose=TRUE) ```

FSA documentation built on July 17, 2021, 5:07 p.m.