![]() ![]() ![]() For a trial of adequate overall size and power there appears to be no statistical advantage to be gained from this approach. As an alternative to having a constant nominal significance level throughout a trial, one could have more stringent significance levels at early stages and less stringent levels at the last one or two analyses. Pocock (1977) applied these repeated significance tests to group. There appears to be little advantage in analysing trial data on more than five occasions unless one anticipates the possibility of an extremely large treatment difference. A group sequential design provides interim analyses before the formal completion of a. Power calculations based on results for normal group sequential designs obtained by numerical integration, enable one to determine the number of patients to be evaluated between analyses. To allow for repeated testing one uses a more stringent (nominal) significance level as a stopping rule. Mehta and Pocock increase sample size to achieve a particular conditional power, calculated under the current estimate of treatment effect: this leads to high increases in sample size for a small range of interim outcomes, whereas we have found it more efficient to make moderate increases in sample size over a wider range of cases. There exist group sequential designs for such trials, on simple approach being to decide in advance on a maximum number of analyses and then to apply repeated significance tests to the accumulating data. For many clinical trials interim analyses are undertaken periodically, one purpose being to determine whether to stop the trial early because of a substantial treatment difference. ![]()
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