R: Power curves for binomial parameterizations

binom.power {binom} | R Documentation

## Power curves for binomial parameterizations

### Description

Uses Wald statistics to compute power curves for several parameterizations.

### Usage

    binom.power(p.alt,
                n = 100,
                p = 0.5,
                alpha = 0.05,
                phi = 1,
                alternative = c("two.sided", "greater", "less"),
                method = c("cloglog", "logit", "probit", "asymp", "lrt", "exact"))

### Arguments

`p.alt` | A vector of success probabilities under the alternative hypothesis.
`n` | A vector representing the number of independent trials in the binomial experiment.
`p` | A vector of success probabilities under the null hypothesis.
`alpha` | A vector of type-I error rates.
`phi` | A vector determining the overdispersion parameter for each binomial experiment.
`alternative` | Type of alternative hypothesis.
`method` | The method used to compute power.

### Details

For derivations see doc/binom.pdf. `p.alt`, `n`, `p`, `alpha`, and `phi` can all be vectors. The length of each argument will be expanded to the longest length. The function assumes the lengths are equal or can be wrapped for multiple values.

### Value

The estimated probability of detecting the difference between `p.alt` and `p`.

### Author(s)

Sundar Dorai-Raj (sdorairaj@gmail.com)

### See Also

`binom.confint`, `binom.bayes`, `binom.logit`, `binom.probit`, `binom.coverage`

### Examples

    binom.power(0.95, alternative = "greater")

[Package binom version 1.1-1 Index]