R: Power and sample size

cloglog.sample.size {binom} | R Documentation

## Power and sample size

### Description

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

### Usage

    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 (sdorairaj@gmail.com)

### See Also

`binom.confint`

### Examples

    cloglog.sample.size(p.alt = 0.8)
    cloglog.sample.size(n = 20)
    cloglog.sample.size(n = 20, power = 0.9)

[Package binom version 1.1-1 Index]