Good practices for quantitative bias analysis
Emory University · Boston University
Abstract
Quantitative bias analysis serves several objectives in epidemiological research. First, it provides a quantitative estimate of the direction, magnitude and uncertainty arising from systematic errors. Second, the acts of identifying sources of systematic error, writing down models to quantify them, assigning values to the bias parameters and interpreting the results combat the human tendency towards overconfidence in research results, syntheses and critiques and the inferences that rest upon them. Finally, by suggesting aspects that dominate uncertainty in a particular research result or topic area, bias analysis can guide efficient allocation of sparse research resources. The fundamental methods of bias…
Citation impact
- FWCI
- 22.38
- Percentile
- 100%
- References
- 85
Authors
6Topics & keywords
- Overconfidence effect
- Publication bias
- Selection bias
- Computer science
- Data science
- Focus (optics)
- Confirmation bias
- Information bias