The next thing you’ll ask, having established your main study question(s), is what is the primary outcome (or primary outcomes) in the study. What is the primary outcome of the study? For example, in an oncology trial, we may want to see if the new treatment reduces mortality, or in a classroom intervention we may be interested in seeing if the intervention improves grades.Įstablishing the study question is vital as it has knock-on effects on all the other assumptions and choices discussed below that will be made when planning the study. It is vital at an early stage we establish “what do we want this study to tell us?”.
The study questions inform what conclusions can be made at the end of the study. It must be established what the study question, or questions are.
In statistical hypothesis terms, power is the probability of rejecting the null hypothesis when it is false. The power is the probability that the study will be able to detect a true effect of a drug or intervention of a specified size or greater. Statistical power is the most commonly used metric for sample size determination. Whether it is the Nature Publishing Group or the Federal Drug Administration (FDA), a study which does not justify its sample size has a higher chance of rejection, scrutiny or failure. Additionally, a study which is too large faces the same ethical problem and will also waste scarce resources such as money, subjects and time.įor these reasons, a sample size justification is a standard part of study design. This is because exposing human subjects or lab animals to the possible risks associated with research is only justifiable if there is a realistic chance that the study will yield useful information. Secondly, studies which are more likely to fail due to inadequate sample size are considered unethical. These estimates will then be less useful in modelling and understanding the real underlying questions of interest in a study. 
This is because a smaller sample size will generate estimates which have higher variation. Why is sample size calculation important?įirstly, a study which is too small is more likely to generate inconclusive, incorrect or spurious results.
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