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Sample Size
Abstract:Conventionally, sample size calculations are viewed as calculations determining the right number of subjects needed for a study. Such calculations follow the classical paradigm: “for a difference X, I need sample size Y.” We argue that the paradigm “for a sample size Y, I get information Z” is more appropriate for many studies and reflects the information needed by scientists when planning a study. This approach applies to both physiological studies and Phase I and II interventional studies. We provide actual examples from our own consulting work to demonstrate this. We conclude that sample size should be viewed not as a unique right number, but rather as a factor needed to assess the utility of a study.
Keywords:Accuracy  Detectable difference  Feasibility  Precision  Scientific thinking
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