Analytic power analysis for correlations (Pearson's r) at different sample sizes

power-analysis-correlations.R

library(tidyverse)
library(pwr)

power_correlation <- function(n, r, alpha=0.05) {
  power <- pwr.r.test(n=n, r=r, sig.level=alpha)
  data.frame(n=n, r=r, alpha=alpha, power=power$power)
}

parameters <- expand.grid(n = seq.int(4, 200, by=2),
                          r = seq.int(.1, .9, by=.1))

results <- pmap_dfr(parameters, power_correlation)

results %>%
  ggplot(aes(n, power, group=r, color=as.factor(r))) +
  geom_line() +
  guides(color = guide_legend(reverse=TRUE)) +
  labs(title = "Power for different sample sizes and correlations",
       x = "Sample size",
       y = NULL,
       color = "Pearson's r")

https://twitter.com/peterdalle/status/1507062984690089985