power_seq: power_seq

In yelleKneK/SMSD: Sequential Methods for Study Design

power_seq

Description

This function calculates the power for a sequence of sample sizes using power for two independent groups when the population standard deviation is assumed known and common across groups.

Usage

power_seq(mu0, mu1, sigma, alpha, n1, n2, n_vals)

Arguments

mu0	Population mean of group 0 (e.g., control).
mu1	Population mean of group 1 (e.g., experimental).
sigma	The population standard deviation, assumed equal across groups.
alpha	The Type I error rate.
n1	The lowest number of samples to consider when generating a sequence of Type II errors.
n2	The highest number of samples to consider when generating a sequence of Type II errors.
n_vals	The number of samples to generate Type II error for.

Value

Returns a series of length "n_vals" of calculated Type II error rates from n1 to n2.

Examples

# Set parameter values
mu0 <- 0
mu1 <- 1
sigma <- 2
alpha <- 0.05
n1 <- 5
n2 <- 50
n_vals <- 10
# Calculate sequence
seq_vals <- power_seq(mu0 = mu0, mu1 = mu1, sigma=sigma, alpha = alpha,
                  n1 = n1, n2 = n2, n_vals = n_vals)

yelleKneK/SMSD documentation built on Nov. 23, 2022, 6:40 p.m.