# cloglog.sample.size

0th

Percentile

##### Power and sample size

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

Keywords
models, htest, univar
##### 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.

binom.confint

##### Aliases
• cloglog.sample.size
##### Examples
cloglog.sample.size(p.alt = 0.8)
cloglog.sample.size(n = 20)
cloglog.sample.size(n = 20, power = 0.9)

Documentation reproduced from package binom, version 1.1-1, License: GPL

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