Adaptive design can affect sample size in several ways:
1. Efficiency: Adaptive design allows for dynamic modifications to the study based on accumulated data. As a result, the sample size required to achieve the study objectives may be optimized, leading to a more efficient allocation of resources.
2. Sample size reassessment: In adaptive designs, interim analyses are conducted during the course of the study to evaluate the accruing data. Based on these analyses, the sample size may be reassessed to ensure that it is sufficient to answer the research question effectively. This reassessment can lead to adjustments in the sample size throughout the study.
3. Reallocation of resources: Adaptive design allows for the reallocation of resources based on the observed treatment effects or other relevant data. If a certain treatment or intervention appears to be highly effective or futile, the sample size for that particular arm can be adjusted accordingly, potentially reducing the required sample size.
4. Sequential nature: Many adaptive designs have a sequential nature, where the sample size is determined in stages or phases, with the option to stop the study early if conclusive results are obtained. This sequential design can reduce the total required sample size compared to traditional fixed designs.
Overall, adaptive design offers the flexibility to modify the study based on accumulating information, potentially resulting in a more streamlined and efficient sample size determination process.
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