Editing P-value (section)

== Related indices ==
The ''E-value'' can refer to two concepts, both of which are related to the p-value and both of which play a role in [[multiple comparisons|multiple testing]]. First, [[E-values|it corresponds to a generic, more robust alternative to the p-value]] that can deal with ''optional continuation'' of experiments. Second, it is also used to abbreviate "expect value", which is the [[Conditional expectation|expected]] number of times that one expects to obtain a test statistic at least as extreme as the one that was actually observed if one assumes that the null hypothesis is true.<ref>{{cite web | url = https://www.ncbi.nlm.nih.gov/blast/Blast.cgi?CMD=Web&PAGE_TYPE=BlastDocs&DOC_TYPE=FAQ#expect | work = National Institutes of Health | title = Definition of E-value }}</ref> This expect-value is the product of the number of tests and the ''p''-value.

The [[Q-value (statistics)|''q''-value]] is the analog of the ''p''-value with respect to the [[False discovery rate#Related concepts|positive false discovery rate]].<ref>{{Cite journal| vauthors = Storey JD |date=2003|title=The positive false discovery rate: a Bayesian interpretation and the q-value|journal=The Annals of Statistics|volume=31|issue=6|pages=2013–2035|doi=10.1214/aos/1074290335|doi-access=free}}</ref> It is used in [[Multiple comparisons problem|multiple hypothesis testing]] to maintain statistical power while minimizing the [[false positive rate]].<ref>{{cite journal | vauthors = Storey JD, Tibshirani R | title = Statistical significance for genomewide studies | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 100 | issue = 16 | pages = 9440–9445 | date = August 2003 | pmid = 12883005 | pmc = 170937 | doi = 10.1073/pnas.1530509100 | doi-access = free | bibcode = 2003PNAS..100.9440S }}</ref>

The [[Probability of Direction|Probability of Direction (''pd'')]] is the [[Bayesian statistics|Bayesian]] numerical equivalent of the ''p''-value.<ref name="makowski2019indices">{{cite journal | vauthors = Makowski D, Ben-Shachar MS, Chen SH, Lüdecke D | title = Indices of Effect Existence and Significance in the Bayesian Framework | journal = Frontiers in Psychology | volume = 10 | pages = 2767 | date = 10 December 2019 | pmid = 31920819 | pmc = 6914840 | doi = 10.3389/fpsyg.2019.02767 | doi-access = free }}</ref> It corresponds to the proportion of the [[Posterior probability|posterior distribution]] that is of the median's sign, typically varying between 50% and 100%, and representing the certainty with which an effect is positive or negative.

[[Second-generation p-values]] extend the concept of p-values by not considering extremely small, practically irrelevant [[effect size]]s as significant.<ref>An Introduction to Second-Generation p-Values Jeffrey D. Blume, Robert A. Greevy, Valerie F. Welty, Jeffrey R. Smith &William D. Dupont https://www.tandfonline.com/doi/full/10.1080/00031305.2018.1537893</ref>