# binom.conf.int: Confidence intervals for binomial counts or proportions In epitools: Epidemiology Tools

## Description

Calculates confidence intervals for binomial counts or proportions

## Usage

 ```1 2 3``` ```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, [email protected], 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.

`pois.exact`, `binom.test`

## Examples

 ```1 2 3``` ```binom.exact(1:10, seq(10, 100, 10)) binom.wilson(1:10, seq(10, 100, 10)) binom.approx(1:10, seq(10, 100, 10)) ```

### Example output

```    x   n proportion       lower     upper conf.level
1   1  10        0.1 0.002528579 0.4450161       0.95
2   2  20        0.1 0.012348527 0.3169827       0.95
3   3  30        0.1 0.021117137 0.2652885       0.95
4   4  40        0.1 0.027925415 0.2366374       0.95
5   5  50        0.1 0.033275094 0.2181354       0.95
6   6  60        0.1 0.037591269 0.2050577       0.95
7   7  70        0.1 0.041159702 0.1952457       0.95
8   8  80        0.1 0.044170940 0.1875651       0.95
9   9  90        0.1 0.046755315 0.1813600       0.95
10 10 100        0.1 0.049004689 0.1762226       0.95
x   n proportion      lower     upper conf.level
1   1  10        0.1 0.01787621 0.4041500       0.95
2   2  20        0.1 0.02786648 0.3010336       0.95
3   3  30        0.1 0.03459989 0.2562108       0.95
4   4  40        0.1 0.03957953 0.2305178       0.95
5   5  50        0.1 0.04347576 0.2136023       0.95
6   6  60        0.1 0.04664283 0.2014946       0.95
7   7  70        0.1 0.04928930 0.1923291       0.95
8   8  80        0.1 0.05154762 0.1851069       0.95
9   9  90        0.1 0.05350675 0.1792417       0.95
10 10 100        0.1 0.05522914 0.1743657       0.95
x   n proportion        lower     upper conf.level
1   1  10        0.1 -0.085938510 0.2859385       0.95
2   2  20        0.1 -0.031478381 0.2314784       0.95
3   3  30        0.1 -0.007351649 0.2073516       0.95
4   4  40        0.1  0.007030745 0.1929693       0.95
5   5  50        0.1  0.016845771 0.1831542       0.95
6   6  60        0.1  0.024090921 0.1759091       0.95
7   7  70        0.1  0.029721849 0.1702782       0.95
8   8  80        0.1  0.034260809 0.1657392       0.95
9   9  90        0.1  0.038020497 0.1619795       0.95
10 10 100        0.1  0.041201080 0.1587989       0.95
```

epitools documentation built on Nov. 17, 2017, 7:58 a.m.