power.lc.mean.bs: Approximates the power of a test for a linear contrast of...

In statpsych: Statistical Methods for Psychologists

Approximates the power of a test for a linear contrast of means for planned sample sizes in a between-subjects design

Description

Computes the approximate power of a test for a linear contrast of population mean for planned sample sizes in a between-subject design. The groups can be the factor levels of a single factor design or the combinations of factors in a factorial design. For a conservatively low power approximation, set the variance planning values to the largest values within their plausible ranges, and set the effect size to a minimally interesting value. The within-group variances can be unequal across groups and a Satterthwaite degree of freedom adjustment is used to improve the accuracy of the power approximation.

Usage

power.lc.mean.bs(alpha, n, var, es, v)

Arguments

alpha	alpha level for hypothesis test
n	vector of planned sample sizes
var	vector of within-group variance planning values
es	planning value of linear contrast of means
v	vector of contrast coefficients

Value

Returns the approximate power of the test

Examples

n <- c(20, 20, 20, 20)
var <- c(70, 70, 80, 80)
v <- c(.5, .5, -.5, -.5)
power.lc.mean.bs(.05, n, var, 5, v)

# Should return:
#          Power
# [1,] 0.7221139

statpsych documentation built on July 9, 2023, 6:50 p.m.