power_Beta: Power Calculations for Test of Two Beta Means

In PASSED: Calculate Power and Sample Size for Two Sample Mean Tests

Power Calculations for Test of Two Beta Means

Description

Compute the power for a test of two sample means with beta distributions, or determine the minimum sample size to obtain a target power.

Usage

power_Beta(n1 = NULL, n2 = NULL, power = NULL, sig.level = 0.05, 
mu1 = NULL, sd1 = NULL, mu2 = NULL, equal.sample = TRUE,
trials = 100, equal.precision = TRUE, sd2 = NULL, 
link.type = c("logit", "probit", "cloglog", "cauchit", "log", "loglog"))

Arguments

n1	sample size in group 1, or sample size in each group if equal.sample = TRUE
n2	sample size in group 2
power	power of test (1 minus Type II error probability)
sig.level	significance level (Type I error probability)
mu1	sample mean of group 1
sd1	standard deviation for group 1
mu2	sample mean of group 2
equal.sample	equal sample sizes for two groups, see details
trials	number of trials in simulation
equal.precision	equal dispersion parameter assumption in simulation
sd2	standard deviation for group 2. Only applicable when equal.precision = FALSE
link.type	type of link used in the beta regression, see details

Details

Exactly one of the parameters n1, n2 and power must be passed as NULL, and that parameter is determined from the others.

This function allows you to set the number of trials in the simulation to control the result accuracy, and type of link used in the beta regression. You can choose one of the following: "logit", "probit", "cloglog", "cauchit", "log", "loglog".

Value

Object of class "power.htest", a list of the arguments (including the computed one) augmented with method and note elements.

Examples

# calculate power
power_Beta(mu1 = 0.5, mu2 = 0.80, sd1 = 0.25, n1 = 60)
# calculate sample size for both groups
power_Beta(mu1 = 0.5, mu2 = 0.80, sd1 = 0.25, power=0.8)

PASSED documentation built on Oct. 16, 2023, 9:07 a.m.