Saville Benjamin R, Kim Yong S, Koch Gary G
Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232-2158, USA.
Pharm Stat. 2011 Jan-Feb;10(1):40-4. doi: 10.1002/pst.407.
For time-to-event data, the power of the two sample logrank test for the comparison of two treatment groups can be greatly influenced by the ratio of the number of patients in each of the treatment groups. Despite the possible loss of power, unequal allocations may be of interest due to a need to collect more data on one of the groups or to considerations related to the acceptability of the treatments to patients. Investigators pursuing such designs may be interested in the cost of the unbalanced design relative to a balanced design with respect to the total number of patients required for the study. We present graphical displays to illustrate the sample size adjustment factor, or ratio of the sample size required by an unequal allocation compared to the sample size required by a balanced allocation, for various survival rates, treatment hazards ratios, and sample size allocation ratios. These graphical displays conveniently summarize information in the literature and provide a useful tool for planning sample sizes for the two sample logrank test.
对于生存时间数据，两个治疗组比较的两样本对数秩检验效能会受到各治疗组患者数量之比的极大影响。尽管可能会损失效能，但由于需要在其中一组收集更多数据，或者出于与治疗对患者的可接受性相关的考虑，不均衡分配可能会受到关注。采用此类设计的研究者可能会对不平衡设计相对于平衡设计在研究所需患者总数方面的成本感兴趣。我们给出图形展示，以说明在各种生存率、治疗风险比和样本量分配比情况下，样本量调整因子，即不均衡分配所需样本量与平衡分配所需样本量之比。这些图形展示方便地总结了文献中的信息，并为两样本对数秩检验的样本量规划提供了有用工具。
