Sample Size: One of the most critical factors affecting statistical power is
sample size. Smaller sample sizes often result in higher variability and lower reliability of results.
Effect Size: The magnitude of the association being studied, also known as
effect size, plays a significant role. Smaller effect sizes require larger sample sizes to achieve adequate power.
Significance Level: The chosen
significance level (alpha) can influence power. A smaller alpha level (e.g., 0.01) will reduce power compared to a larger alpha level (e.g., 0.05).
Measurement Error: Poor measurement techniques or instrument inaccuracies can introduce
measurement error, thereby reducing power.
Study Design: The design of the study, including
randomization and control of confounding variables, can also affect power.
