Concerns about rigor in science, particularly obesity research, have been raised in recent years, and a movement is underway to proactively help investigators structure the design and reproducibility of their science.
A paper from investigators at the University of Alabama at Birmingham recently published in Obesity identifies several key statistical errors commonly seen in obesity research with discussions on how to identify and avoid making these mistakes.
“Our goal is to provide researchers and reviewers with a tutorial to improve the rigor of the science in future obesity studies,” said Brandon George, PhD, statistician in the University of Alabama at Birmingham Office of Energetics. “Investigators who conduct primary research may find the paper useful to read or share with statistical collaborators to obtain a deeper understanding of statistical issues, avoid making the discussed errors, and increase the reproducibility and rigor of the field. Editors, reviewers and consumers will find valuable information allowing them to properly identify these common errors while critically reading the work of others.”
Most notable are errors related to tests of pre-post differences between groups, inappropriate design or analysis of cluster randomized trials, and calculation errors in meta-analyses. Ten of the most common types of statistical errors stem from errors in statistical design, analysis, interpretation and reporting. George and colleagues further discuss ways to identify, avoid and correct such errors when researching obesity.
Ten common errors in obesity research include:
- Misinterpretation of statistical significance
- Inappropriate testing against baseline values
- Excessive and undisclosed multiple testing and “p-value hacking”
- Mishandling of clustering in cluster randomized trials
- Misconceptions about nonparametric tests
- Mishandling of missing data
- Miscalculation of effect sizes
- Ignoring regression to the mean
- Ignoring confirmation bias
- Insufficient statistical reporting
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- Research Center: University of Alabama at Birmingham
- Featured NORC Member(s): Brandon George, PhD, Biostatistician of Energetics