powr: Estimation of power for unpaired and paired t-test.

In AlexanderRitz/pairedpowR: Power Estimation for paired data

Description

Estimates the power of paired and unpaired t-test in the case of normal data for a given intra-pair correlation, significance level, sample size and effect size.

Usage

powr(npairs = NULL, eff = NULL, rho = NULL, sig = 0.05, rounds = 10000)

Arguments

npairs	integer. Supplies the number of pairs to be simulated. Resulting in two samples of size "npairs".
eff	numeric. Supplies the difference in means between both groups. Can be interpreted as effect size based on the fact that standard normal variates are the basis of simulation.
rho	numeric. Supplies the correlation coefficient between both groups.
sig	numeric. Supplies the significance level for the test. 0.05 by default.
rounds	integer. Supplies the number of simulation to base the power estimation on. Set to 10000 by default.

Value

Returns the estimated power for both tests as a vector containing the power of the unpaired t-test in the first place.

Examples

powertest <- powr(npairs = 10, eff = 0.5, rho = 0.1)
powertest

AlexanderRitz/pairedpowR documentation built on March 16, 2020, 12:16 a.m.