Welcome to our research page featuring recent publications in the field of biostatistics and epidemiology! These fields play a crucial role in advancing our understanding of the causes, prevention, and treatment of various health conditions. Our team is dedicated to advancing the field through innovative studies and cutting-edge statistical analyses. On this page, you will find our collection of research publications describing the development of new statistical methods and their application to real-world data. Please feel free to contact us with any questions or comments.
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Hernán, using a hypothetical example, argues that policies that prevent researchers from conducting underpowered observational studies using existing databases are misguided explaining that "[w]hen a causal question is important, it is preferable to have multiple studies with imprecise estimates than having no study at all." While we do not disagree with the sentiment expressed, caution is warranted. Small observational studies are a major cause of distrust in science, mainly because their results are often selectively reported. The hypothetical example used to justify Hernán's position is too simplistic and overly optimistic. In this short response, we reconsider Hernán's hypothetical example and offer a list of other factors - beyond simply the importance of the question - that are relevant when deciding whether or not to pursue underpowered research.