#statstab #234 Not all alphas can be justified

Thoughts: When using discrete distributions, with few outcomes, your alpha cannot always take the values you want. Same with the distribution of p-values under the null.

#pvalues #nhst #errorcontrol #alpha

https://osf.io/preprints/psyarxiv/erwvk

#statstab #189 Post Hoc Power: Not Empowering, Just Misleading

Thoughts: "the observed power is a 1:1 function of the P value" If you need a ref for why "post hoc" power is nonsense (paywalled).

#power #posthoc #QRPs #errorcontrol #poweranalysis

https://www.sciencedirect.com/science/article/pii/S0022480420305023

#statstab #186 Are Multiple Contrast Tests Superior to the ANOVA?

Thoughts: Focuses more on the statistical aspects of the comparison than the theoretical ones. But insightful for newbies.

#nhst #anova #ttest #errorcontrol
#typeI #pvalues

https://www.degruyter.com/document/doi/10.1515/ijb-2012-0020/html?lang=en

#statstab #127 Optimal test procedures for multiple hypotheses controlling the familywise expected loss

Thoughts: Can't wait to see papers defining their own loss functions to control error rates 🙄.

#errorcontrol #typeI #NHST #pvalues #stats

https://onlinelibrary.wiley.com/doi/10.1111/biom.13907

#statstab #84 Using the data twice

Thoughts: A very good overview of conditional and unconditional inferences based on the modelling decisions we make. I can't say I've seen many discuss this.

#errorcontrol #inference #modelling #stats

https://www.alexpghayes.com/post/2020-05-04_using-the-data-twice/

#statstab #74 When to adjust alpha during multiple testing: disjunction, conjunction, and individual testing by @MarkRubin

Thoughts: Error control = NHST. But doing it right is a nightmare. This paper made sense to me.

#NHST #pvalues #errorcontrol

https://doi.org/10.1007/s11229-021-03276-4