ABSTRACT

The weighted log-rank class is the common and widely used class of two-sample tests for clustered data. Clustered data with censored failure times often arise in tumorigenicity investigations and clinical trials. The randomized block design is a significant design that reduces both unintentional bias and selection bias. Accordingly, the p-values of the null permutation distribution of weighted log-rank class for clustered data are approximated using the double saddlepoint approximation technique. Comprehensive simulation studies are carried out to appraise the accuracy of the saddlepoint approximation. This approximation exhibits a significant improvement in precision over the asymptotic approximation. This precision motivates us to determine the approximated confidence intervals for the treatment impact.

摘要

加权对数秩类是常见且广泛使用的聚类数据双样本检验类。在致瘤性研究和临床试验中经常出现具有删失失败时间的聚类数据。随机区组设计是一种重要的设计，可以减少无意偏差和选择偏差。因此，使用双鞍点近似技术来近似聚类数据的加权对数秩类的空置换分布的p值。进行了全面的模拟研究以评估鞍点近似的准确性。这种近似比渐近近似在精度上有显着提高。这种精度促使我们确定治疗影响的近似置信区间。