@misc{9678170cdf794639b66a03998c1f02d0,
title = "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 = "Bayesian, Effect size, Power analysis, Sample size, Type I error rate, Type II error rate, Bayesian, Effect size, Power analysis, Sample size, Type I error rate, Type II error rate",
author = "Mirco Bundschuh and Newman, \{Michael C.\} and Zubrod, \{Jochen P.\} and Frank Seitz and Rosenfeldt, \{Ricki R.\} and Ralf Schulz",
year = "2015",
doi = "10.1007/s11356-014-3749-z",
language = "English",
volume = "22",
series = "Environmental Science and Pollution Research",
publisher = "Springer Heidelberg",
number = "5",
address = "Germany",
type = "Other",
}