# cloglog.sample.size: Power and sample size In binom: Binomial Confidence Intervals For Several Parameterizations

## Description

Power and sample size for a binomial proportion using the cloglog parameterization.

## Usage

 ```1 2 3``` ```cloglog.sample.size(p.alt, n = NULL, p = 0.5, power = 0.8, alpha = 0.05, alternative = c("two.sided", "greater", "less"), exact.n = FALSE, recompute.power = FALSE, phi = 1) ```

## Arguments

 `p.alt` The alternative proportion in a one-sample test. `n` The sample size in a one-sample test. `p` The null proportion in a one-sample test. Default is 0.5. `power` The desired power level. Default is 0.80. `alpha` The desired alpha level - probability of a Type I error. Default is 0.05. `alternative` Nature of alternative hypothesis. One of "two.sided", "greater", "less". `exact.n` logical; If `TRUE`, the computed sample size will not be rounded up. Default is `FALSE`. `recompute.power` logical; If `TRUE`, after the sample size is computed, the power will be recomputed. This is only advantageous when the sample size is rounded up. Default is `FALSE`. `phi` Dispersion parameter by which to inflate (`phi > 1`) or deflate (`phi < 1`) variance. Default is 1.

## Details

This function can be used to calculate sample size, power or minimum detectable difference. It determines what to compute base on the arguments provided. If `p.alt` is given, but `n` is not, then sample size is computed. If `p.alt` is given along with `n`, then the power is computed. If only `n` is provided, the minimum detectable difference is computed using the default power of 0.80.

## Value

A `data.frame` containing the power, sample size and all of the input which was used to perform the computations.

## Author(s)

Sundar Dorai-Raj ([email protected])

`binom.confint`
 ```1 2 3``` ```cloglog.sample.size(p.alt = 0.8) cloglog.sample.size(n = 20) cloglog.sample.size(n = 20, power = 0.9) ```