Sample size for a test of a slope — size.test.slope • statpsych

Computes the total sample size required to test a population slope with desired power in a between-subjects design with a quantitative factor. In an experimental design, the total sample size would be allocated to the levels of the quantitative factor and it might be necessary to use a larger total sample size to achieve equal sample sizes. Set the error variance planning value to the largest value within a plausible range for a conservatively large sample size.

For more details, see Section 1.25 of Bonett (2021, Volume 2)

Usage

size.test.slope(alpha, pow, evar, x, slope, h)

Arguments

alpha: alpha level for hypothesis test
pow: desired power
evar: planning value of within-group (error) variance
x: vector of x values of the quantitative factor
slope: planning value of slope
h: null hypothesis value of slope

Value

Returns the required total sample size

References

Bonett DG (2021). Statistical Methods for Psychologists https://dgbonett.sites.ucsc.edu/.

Examples

x <- c(2, 5, 8)
size.test.slope(.05, .9, 31.1, x, .75, 0)
#>  Total sample size
#>                100

# Should return:
# Total sample size
#               100