Power analysis is used in the estimation of sample sizes for experimental designs. Most programs and R packages will only output
the highest recommended sample size to the user. Often the user input can be complicated and computing multiple power analyses
for different treatment comparisons can be time consuming. This package simplifies the user input and allows the user to
view all of the sample size recommendations or just the ones they want to see. Currently, one-way ANOVAs
and factorial ANOVAs
n.multiway are supported. The effect size utilized by the functions is eta-squared which
is equivalent to percentage variance. It is used in the input for all of the functions so that the user may use one standard effect
size for all of their calculations. The calculations used to calculate the recommended sample sizes are from the 'pwr'
package. Future updates are planned to add more experimental designs.
|Author:||Aaron McGarvey email@example.com|
|Maintainer:||Aaron McGarvey firstname.lastname@example.org|