Calculating study power involves several steps and often utilizes statistical software:
Define Parameters: Specify the expected effect size, significance level (α), and the desired power (typically 80% or 90%). Estimate Variability: Use previous studies or pilot data to estimate the variability within your measurements. Use Power Calculations: Employ statistical formulas or software tools to calculate the necessary sample size to achieve the desired power. Common tools include G*Power, PASS, and statistical packages like R and SAS.
