generate table of required sample sizes for various correlation effect sizes and various levels of desired power in a study

correlation_power_calculations.R

# generate table of required sample sizes for various correlation effect sizes
# and various levels of desired power in a study

# you need the pwr package
library(pwr)

# vector of effect sizes to explore
effect_sizes <- seq(from = 0.05, to = 0.95, by = 0.05)

# vector of desired power
power <- seq(from = 0.8, to = 0.95, length.out = 4)

# initialise matrix to store final results in
sim_results <- matrix(0, nrow = length(effect_sizes), 
                      ncol = length(power))

# change the column & row names accordingly
rownames(sim_results) <- effect_sizes
colnames(sim_results) <- power

# sample size determination starts here
# for each effect size...
for(i in 1:nrow(sim_results)){
  
  # for each level of desired power...
  for(j in 1:ncol(sim_results)){
    # calculate the sample size for current effect size & power
    curr_power <- pwr.r.test(r = effect_sizes[i], 
                             power = power[j], 
                             sig.level = 0.05, 
                             alternative = "two.sided")
    # store the resulting sample size in the matrix
    sim_results[i, j] <- round(curr_power$n, 0)
  }
}

# save all to a csv file
write.csv(sim_results, "correlation_power.csv")