We also estimated EEE power when the sample size of the available study is larger than the sample size of the planned study with α level constant for both studies. In general, EEE performed very well. The exception occurred when the initial simulated power was very close to 1.0 (e.g., 0.99999), and had been rounded off to ‘1’. This makes the inverse of the standard normal distribution function Φ−1(•) to be infinite. Hence the EEE formula cannot be applied when power is reported as 1.0 and is dubious if the inputted simulation power is 0.99 or greater. Note that this is not a limitation of EEE, but a limitation of the data that are provided. Once we remove such data points, it is clear that the EEE approximated values and the simulated values are once again in very close concordance (Figure 2). After removing the observations where simulated power was 1.0, we had a total of 504 observations and the CCC between simulated study power and EEE approximated power was 0.9939 (95% CI 0.9927 – 0.9948) and Pearson correlation coefficient
