2019-02-01

Andrew Brown, Ph.D., Department of Epidemiology and Biostatistics, Indiana University

"Statistical and inferential issues in nutrition and obesity research: opportunities for quantitative reasoning"

The causes and correlates of the seemingly intractable obesity epidemic are investigated by numerous studies every year, from pre-clinical work to interventions to population modeling. Although the literature contains many great examples of quality studies, key errors continue to be made at a non-negligible rate. Such errors may be able to be mitigated, at least in part, by increased quantitative and statistical reasoning in the fields of nutrition and obesity. I will present examples of errors that we have observed in the literature and the quantitative or statistical principles on which they are based. These include: errors involving long-established statistical principles; errors that could have been avoided with quantitative reasoning; and more complex, less intuitive errors. The errors will be used to illustrate the potential for quantitative scientists to contribute to more rigorous nutrition and obesity science.

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