Com-Nougue C, Rodary C
Unité de recherche sur l'épidémiologie des cancers (U. 287), Institut Gustave Roussy, Villejuif.
Rev Epidemiol Sante Publique. 1987;35(5):416-30.
The absence of a significant difference in a classical efficacy trial testing the null hypothesis of equality between N and S does not allow us to conclude that the treatments are equivalent. Testing the null hypothesis of N not equivalent to S requires: specifying the definition of "equivalence" by choosing delta L, the upper allowable value of the actual difference between two equivalent treatments. The appropriate statistic D which evaluates the difference between N and S, has a non central distribution under the null hypothesis of inequivalence (Ko:[E(D)] greater than or equal to delta L, two-sided test). Under the null hypothesis for a two-sided test, parameters of noncentral distribution have to be estimated, and the critical p-value is obtained using some approximation. Confidence interval of the true difference delta can also provide a decision rule. Specific calculation of the minimum number of subjects is required when designing an equivalence trial.
在一项检验N和S相等这一零假设的经典疗效试验中，若未发现显著差异，我们不能就此得出两种治疗方法等效的结论。检验N与S不等效的零假设需要：通过选择δL（两种等效治疗方法实际差异的上限允许值）来明确“等效性”的定义。用于评估N和S之间差异的合适统计量D，在不等效零假设下具有非中心分布（Ko：[E(D)]≥δL，双侧检验）。在双侧检验的零假设下，必须估计非中心分布的参数，并使用某种近似方法获得临界p值。真实差异δ的置信区间也可提供决策规则。设计等效性试验时需要具体计算所需的最少受试者数量。
