Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
University of California, Los Angeles · Luxembourg Institute of Health · +9 more institutions
Abstract
Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. A key problem is that there are no interpretations of these concepts that are at once simple, intuitive, correct, and foolproof. Instead, correct use and interpretation of these statistics requires an attention to detail which seems to tax the patience of working scientists. This high cognitive demand has led to an epidemic of shortcut definitions and interpretations that are simply wrong, sometimes disastrously so-and yet these misinterpretations dominate much of the scientific literature. In light of this problem, we provide definitions and a discussion of basic…
Citation impact
- FWCI
- 196.07
- Percentile
- 100%
- References
- 136
Authors
7- SGSander GreenlandCorresponding
University of California, Los Angeles
- SSStephen Senn
Luxembourg Institute of Health
- KJKenneth J. Rothman
RTI International, RTI Health Solutions
- JBJohn B. Carlin
University of Melbourne, Murdoch Children's Research Institute
- CPCharles Poole
University of North Carolina at Chapel Hill
Topics & keywords
- Interpretation (philosophy)
- Statistical power
- Statistical hypothesis testing
- Presentation (obstetrics)
- Confidence interval
- Explanatory power
- p-value
- Statistics
- Good health and well-being