![]() These are illustrated in the following table for an overall significance level of \(\alpha = 0.05\) and for R = 2,3,4,5. There are primarily three schemes for selecting the boundary points which have been proposed. The boundary points are chosen such that the overall significance level does not exceed the desired \(\alpha\). At the \(r^\) interim analysis, the clinical trial is terminated with rejection of the null hypothesis if: Also, we let \(B_1, \dots, B_R\) denote the corresponding boundary points (critical values). We are adding to the dataset and analyzing the current set that has been collected. Suppose that the group sequential approach consists of R analyses, and we let \(Z_1, \dots, Z_R\) denote the test statistic at the R times of hypothesis testing. Again, let's focus more on the concepts than the statistical details. The group sequential analysis is defined as the situation in which only a few scheduled analyses are conducted. Usually this frequency of interim analyses detects treatment effects nearly as early as continuous monitoring. In fact, for most multi-center clinical trials, interim statistical analyses are conducted only once or twice per year. In most clinical trials, it is not necessary to perform a statistical analysis after each patient is accrued. Therefore, the frequentist approach to interim monitoring of clinical trials focuses on controlling the type I error rate. From a frequentist point of view, repeated hypothesis testing of accumulating data increases the type I error rate of a clinical trial.
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