Some readers might encounter obstacle in the determination of non-inferiority/equivalence/superiority margin. Which readers need to know is about the choice of null and alternative hypothesis, which should be adjusted according the study objective. Thirdly, the sample size can be estimated based on several reasonable parameters. Gather the data of relevant parameters of interest but sometimes a The null and alternative hypotheses, along with the type I error rateĪnd the power (1- type II error rate). Indeed, the steps for calculating sample size mirror the steps The type I error is usually set at two sided 0.05, not all, but some To be conservative, a two-sided test is usually conductedĬompared to one-sided test, which requires smaller sample size. Then the chances of difference occurring due to “chance” are very One reason is that a real difference exists between the two interventions and the other reason is that thisĭifference is by chance, but there is only 3% chance that this difference is just by chance. Significant difference can exist simultaneously (assuming that allīias have been controlled). ![]() ![]() For example, we predefined a statistical significance level of α =0.05, a positive P value equaled 0.03 was foundĪt the end of a completed two-arm trial. I error (rejecting the null hypothesis when it is actually true) isĬalled α (alpha). There’s no such thing as “my results are right” but rather “how much error I am committing”.The probability of committing a type In classical statistical terms, type I error is always associated
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