Assessing the Probability That a Positive Report is False: An Approach for Molecular Epidemiology Studies
National Institutes of Health · National Cancer Institute · +1 more institution
Abstract
Too many reports of associations between genetic variants and common cancer sites and other complex diseases are false positives. A major reason for this unfortunate situation is the strategy of declaring statistical significance based on a P value alone, particularly, any P value below.05. The false positive report probability (FPRP), the probability of no true association between a genetic variant and disease given a statistically significant finding, depends not only on the observed P value but also on both the prior probability that the association between the genetic variant and the disease is real and the statistical power of the test. In this commentary, we show how to assess the FPRP and how to use it…
Citation impact
- FWCI
- 66.37
- Percentile
- 100%
- References
- 37
Authors
5- SWSholom WacholderCorresponding
National Institutes of Health, National Cancer Institute, Department of Health and Human Services
- SJStephen J. Chanock
National Cancer Institute, Department of Health and Human Services
- MGMontserrat García‐Closas
National Institutes of Health
- LELaure El ghormli
National Institutes of Health, National Cancer Institute, Department of Health and Human Services
- NRNathaniel Rothman
National Institutes of Health, National Cancer Institute, Department of Health and Human Services
Topics & keywords
- False positive paradox
- Epidemiology
- Disease
- Medicine
- Statistical power
- Value (mathematics)
- p-value
- Statistical hypothesis testing
- Good health and well-being