Power and sample size
Power and sample size for a binomial proportion using the cloglog parameterization.
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)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 |
recompute.power |
logical; If |
phi |
Dispersion parameter by which to inflate ( |
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.
A data.frame containing the power, sample size and all of the
input which was used to perform the computations.
Sundar Dorai-Raj (sdorairaj@gmail.com)
cloglog.sample.size(p.alt = 0.8) cloglog.sample.size(n = 20) cloglog.sample.size(n = 20, power = 0.9)
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