Exploring The Power Of Curve Manipulation In R Curvy
Comparing different power curves (based on. In the vast world of r programming, there are numerous functions that provide powerful capabilities for data visualization and analysis. One such function that often goes under. Using this, we can then perform a power analysis for each combination of effect size and sample size to create our power curves. The estimated power of a given test can be reported with a table or with a curve in a plot.
We’ll specify the power model: Y ~ i(x^power) and make a starting guess that it’s a linear relation, i. e. That the power is 1. Note the use of the i operator to specify that the ^ exponentiation. Calculate power curves description. Calculate and optionally plot power curves for different effect sizes and trial counts. This function takes a usage
