The p-value and its implicit symbolism
The Aristotelian syllogistic logic behind the Fisherian p-value is ubiquitously misunderstood. This can lead to various fallacious logical inferences. The p-value resembles a Kantian paralogism, i.e., the metric appears objective and logically valid, even though it is not. The reliance on the p-value is an irrational social ritual (cf. Gigerenzer, 2004). Social conformity, obedience to authority, groupthink, and other aspects of Social Identity Theory (SIT) play an important role in this context.
Given the well-documented paralogisms associated with classical Fisherian null hypothesis significance testing (cf. Cohen, 1994) I advocate alternative inferential research methods. For the statistical analyses of the experimental data I collected during my PhD I utilised Bayesian bootstrapping, Bayes Factor analysis, and Bayesian parameter estimation via Markov chain Monte Carlo simulations (in addition to classical NHST).
“Few researchers are aware that their own heroes rejected what they practice routinely. Awareness of the origins of the ritual and of its rejection could cause a virulent cognitive dissonance, in addition to dissonance with editors, reviewers, and dear colleagues. Suppression of conflicts and contradicting information is in the very nature of this social ritual.”
(Gerd Gigerenzer, 2004, p. 592; Director Emeritus of the Center for Adaptive Behavior and Cognition at the Max Planck Institute for Human Development, inter alia)
- Cohen, J. (1994). The Earth Is Round (p < .05). American Psychologist, 49(12), 997–1003. https://doi.org/https://doi.org/10.1037/0003-066X.49.12.997
- Gigerenzer, G. (2004). Mindless statistics. Journal of Socio-Economics, 33(5), 587–606. https://doi.org/10.1016/j.socec.2004.09.033
Statistical Research Methods workshop at the University of Plymouth in 2014:
The pitfalls of hypothesis testing
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Fullscreen: https://christopher-germann.de/papers/pitfalls-of-nhst/
handout-nhst
See also: https://christopher-germann.de/the-paralogisms-of-null-hypothesis-significance-testing-in-science/
