With the advent of administrative databases and patient registries, big data is increasingly accessible to researchers. The large sample size of these data sets make the study of rare outcomes easier and provide the potential to determine national estimates and regional variations. As such, the JAMA Surgery editors and reviewers have seen more submissions using big data to answer clinical and policy-related questions. However, no database is completely free of bias and measurement error. With bigger data, random signals may denote statistical significance, and precision may be incorrectly inferred because of narrow confidence intervals. While many principles apply to all studies, the importance of these methodological issues is amplified in large, complex data sets.
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Kaji AH, Rademaker AW, Hyslop T. Tips for Analyzing Large Data Sets From the JAMA Surgery Statistical Editors. JAMA Surg. Published online April 04, 2018. doi:10.1001/jamasurg.2018.0647
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