![]() ![]() 'Absence of evidence is not evidence of absence' 1) is a free article which contains practical examples, and I highly recommend it to be read. Many authors make the same mistakes and researchers warn against this kind of mistake. This is clearly a fault because whether a significant difference exists or not, the size of the samples is too small to make a conclusion. There are some articles that draw a conclusion that there is no difference between two groups because p > 0.05, without calculating sample size. Simply, to save time and money, researchers should calculate the sample size.Īs researchers usually want to prove that the experimental group is superior to the control group, this article will focus on the superiority trial and we will discuss the non-inferiority trials next time. ![]() Indeed, researchers should know how to calculate sample size because they have limited time and money. Rather, sample size calculation is an indispensable process for obtaining optimal results. Also, they think it is too hard to calculate because they need to use complicated formulas. Some of them even treat it as a kind of rite of passage. It is thought by some researchers that if they conduct a sample size calculation, they need to investigate a high number of samples whereas they only have limited time and money. Still, many clinicians need to learn why the sample size needs to be calculated and how to calculate it. In recent years, as the institutional review board has become mandatory, estimation of the sample size has attracted people's attention. ![]()
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