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August 22/29, 2012

The Value of Statistical Analysis Plans in Observational Research: Defining High-Quality Research From the Start

Author Affiliations

Author Affiliations: Department of Biostatistics and Bioinformatics, Duke University School of Medicine (Dr Thomas), and Duke Clinical Research Institute (Dr Peterson), Durham, North Carolina. Dr Peterson is also Contributing Editor, JAMA.

JAMA. 2012;308(8):773-774. doi:10.1001/jama.2012.9502

The increasing availability of electronic health data combined with federal investment has stimulated an expansion in observational clinical research.1 Observational studies can complement clinical trials and provide important information about comparative safety and effectiveness in populations not well studied in clinical trials. However, there are numerous examples in which the findings from observational studies have failed to be replicated.2 These failures may be due to several factors, including the exploratory nature of observational questions, failure to fully account for treatment selection bias, known publication biases, and the tendency to pursue post hoc hypotheses. This later problem, termed data dredging, is facilitated by the lack of fidelity to a prespecified hypothesis and inadequate reporting of the actual analytic process.

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