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Simulation techniques use repeated random sampling from statistical models to emulate trial behavior under a range of assumptions. They’re especially useful when analytical formulas are unavailable or complex due to the study’s design.
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In multi-arm trials, each comparison of an experimental group to control must maintain sufficient power. However, sharing a control arm introduces dependencies, and adjusting for multiple comparisons is essential to control the family-wise error rate (FWER).
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Bayesian methods focus on the probability of achieving a desired posterior result, given the trial data and prior information.
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Regulatory agencies require that clinical trials:
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SSR is a statistical method that allows modification of the initially planned sample size during a trial based on interim data. It ensures the study maintains adequate power despite uncertainties in assumptions like effect size or variability.
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Regulatory authorities assess whether a trial’s sample size:
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An interim analysis is a statistical assessment of trial data performed before the trial’s scheduled end. It is typically carried out by an independent body such as a Data Monitoring Committee (DMC) or Data Safety Monitoring Board (DSMB).
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A group sequential design is a type of adaptive trial design that allows for interim analyses at pre-specified points during the trial. These “looks” at the data help assess early evidence of benefit or futility while preserving the overall Type I error rate.
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A DMC is an independent body tasked with periodic review of trial data to protect participant safety and ensure the scientific integrity of the study. DMCs are especially relevant in large, long-duration, or high-risk trials involving vulnerable populations or novel therapies.
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Blinding refers to concealing treatment allocations from participants, investigators, and other trial personnel to prevent bias in outcome assessments, data collection, and trial management.
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