Addendum to the article: Misuse of null hypothesis significance testing: Would estimation of positive and negative predictive values improve certainty of chemical risk assessment?

Abstract

We argued recently that the positive predictive value (PPV) and the negative predictive value (NPV) are valuable metrics to include during null hypothesis significance testing: They inform the researcher about the probability of statistically significant and non-significant test outcomes actually being true. Although commonly misunderstood, a reported p value estimates only the probability of obtaining the results or more extreme results if the null hypothesis of no effect was true. Calculations of the more informative PPV and NPV require a priori estimate of the probability (R). The present document discusses challenges of estimating R.

Keywords

Sample size; Bayesian; Power analysis; Effect size; Type I error rate; Type II error rate

Published in

Environmental Science and Pollution Research
2015, volume: 22, number: 5, pages: 3955-3957
Publisher: SPRINGER HEIDELBERG

SLU Authors

• Bundschuh, Mirco

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    
  • University of Koblenz-Landau

UKÄ Subject classification

Other Biological Topics

Publication identifier

• DOI: https://doi.org/10.1007/s11356-014-3749-z

Permanent link to this page (URI)

https://res.slu.se/id/publ/68255