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

Source: R/statpsych1.R

Computes the approximate power of a test for a linear contrast of population means 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.

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)
#>      Power
#>  0.7221171

# Should return:
#     Power
# 0.7221171