What factors influence the calculation of sample size for a trial?

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The main idea is that sample size is determined by statistical planning to ensure a study has enough data to detect a real treatment effect if it exists. The crucial inputs are the expected effect size you want to be able to detect, the significance level you’re willing to accept (the chance of a false positive), the desired power (chance of finding a true effect), and how variable the outcome is. The design of the study matters as well—whether it’s parallel or cross-over, how many groups, and any clustering or unequal allocation. If you expect participants to drop out or not adhere to the protocol, you inflate the initial sample to preserve power. External factors like budget or the number of investigators affect feasibility and logistics, but they do not set the statistical requirements for the number of participants needed.