compute_sample_size: Compute sample size

In Nth-iteration-labs/ssev: Sample Size Computation for Fixed N with Optimal Reward

Description

Function to compute the optimal sample size for a comparison of two means (with equal or unequal variances) or proportions. Function returns the standard sample size for an RCT with the specified power, as well as the optimal sample size for a population of size N.

Usage

compute_sample_size(means = NULL, sds = NULL, proportions = NULL,
  N = Inf, power = 0.8, sig.level = 0.05, ties = 0.5,
  .verbose = FALSE, ...)

Arguments

means	A vector of length 2 containing the (assumed) means of the two groups
sds	A vector containing the (assumed) standard deviations of the two groups. When only one element is supplied equal variances are assumed.
proportions	A vector of length 2 containing the (assumed) proportions of the two groups
N	Estimated population size
power	Desired power for the classical RCT
sig.level	Significance level of the test used (alpha)
ties	Probability of choosing the first group in case of a tie (i.e., H0 is not rejected)
.verbose	Whether or not verbose output should be provided, default FALSE
...	further arguments passed to or from other methods.

Value

An object of type ssev

Examples

compute_sample_size(means=c(0,1), sds=2, N=100)
compute_sample_size(means=c(0,1), sds=2, N=10000, power=.9)
compute_sample_size(means=c(0,1), sds=c(1,2), N=10000)
compute_sample_size(proportions=c(.5,.7), N=5000)

Nth-iteration-labs/ssev documentation built on May 9, 2019, 10:39 a.m.