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The number of treatment units (subjects or groups of subjects) assigned to control and treatment groups, affects an RCT's reliability. If the effect of the treatment is small, the number of treatment units in either group may be insufficient for rejecting the null hypothesis in the respective statistical test. The failure to reject the null hypothesis would imply that the treatment shows no statistically significant effect on the treated in a given test. But as the sample size increases, the same RCT may be able to demonstrate a significant effect of the treatment, even if this effect is small.

The number of treatment units (subjects or groups of subjects) assigned to control and treatment groups, affects an RCT's reliability. If the effect of the treatment is small, the number of treatment units in either group may be insufficient for rejecting the null hypothesis in the respective statistical test. The failure to reject the null hypothesis would imply that the treatment shows no statistically significant effect on the treated in a given test. But as the sample size increases, the same RCT may be able to demonstrate a significant effect of the treatment, even if this effect is small.

分配给控制组和治疗组的治疗单位(受试者或受试者组)的数量影响 RCT 的可靠性。如果治疗的效果很小，任何一组的治疗单位的数量都可能不足以在各自的统计检验中拒绝无效假设。拒绝零假设的失败将意味着治疗在给定的测试中对治疗没有统计学意义上的显著影响。但是随着样本量的增加，相同的随机对照试验也许能够证明治疗的显著效果，即使这种效果很小。

分配给控制组和治疗组的治疗单位(受试者或受试者组)的样本量影响 RCT 的可靠性。如果治疗的效果很小，任何一组的治疗单位的样本量都可能不足以在各自的统计检验中拒绝无效假设（零假设）。拒绝零假设的失败将意味着治疗在给定的测试中对治疗没有统计学意义上的显著影响。但是随着样本量的增加，相同的随机对照试验也许能够证明治疗的显著效果，即使这种效果很小。

== Blinding ==

== Blinding ==