#statstab #521 Non-adjustment for multiple testing in multi-arm trials of distinct treatments: Rationale and justification

Thoughts: Most researchers struggle with multiplicity corrections.

#error #bonferroni #FWER #FDR #falsepositive #nhst #alpha

https://pmc.ncbi.nlm.nih.gov/articles/PMC7534018/

#statstab #518 Before p < 0.05 to Beyond p < 0.05: Using History to
Contextualize p-Values and Significance Testing

Thoughts: An appropriate paper for today.

#pvalues #teaching #history #pedagogy #nhst #fisher

https://www.tandfonline.com/doi/pdf/10.1080/00031305.2018.1537891

Beyond the p Value: Reform Spreads Across the World and Across Disciplines

...as evidenced by this article from Brazil, which I'm delighted to see:

The article's header

I salute Karen Grimmer, JECP co-editor, for publishing it,

https://thenewstatistics.com/itns/2026/03/04/beyond-the-p-value-reform-spreads-across-the-world-and-across-disciplines/

#NHST #OpenScience #Replication #StatisticalReform

#statstab #489 On the performance of the Neyman Allocation with small pilots

Thoughts: If you know your treatment condition will have larger variance you can optimise your sample size.

#nhst #samplesize #neynan #heterogeneity #welch #variance #pilot #se

https://www.sciencedirect.com/science/article/pii/S0304407624001398

#statstab #487 More than meets the ITT: A guide for anticipating and investigating nonsignificant results in survey experiments

Thoughts: I see a lot of papers that make at least one of the 7 errors for "no effect".

#survey #nhst #nulleffects #nonsignificant #pvalue #power

https://doi.org/10.1017/XPS.2024.1

#statstab #478 Equivalence Tests {marginaleffects}

Thoughts: Often you want to test "no difference" in more complex models than many packages or software permit.
With a few lines of code you can do that for most models.

#Equivalence #noeffect #rstats #TOST #EQ #NHST #hypothesistesting

https://marginaleffects.com/chapters/predictions.html#sec-predictions_visualization

#statstab #476 Experimental : causal

Thoughts: Randomized experiments are the gold standard for inference for a reason. But they are hard to design.

#design #r #statistics #methods #experiment #tutorial #pedagogy #education #hypothesis #nhst #causal #ancova

https://book.declaredesign.org/library/experimental-causal.html

#statstab #467 Replication, statistical consistency, and publication bias

Thoughts: Is the replication of a a finding the "gold standard" for scientific discovery? Maybe not.

#replication #metascience #metapsychology #statistics #bias #QRPs #nhst

https://doi.org/10.1016/j.jmp.2013.02.003

Thankyou Jiangang! A Ten-Year Journey to Significance Roulette

Jiangang Xia is an enterprising professor at the University of Nebraska who, among many other things, teaches into China. He alerted me some years ago to the difficulty his students in China had accessing my videos because YouTube was blocked for them. So I mou

https://thenewstatistics.com/itns/2026/01/16/thankyou-jiangang-a-ten-year-journey-to-significance-roulette/

#ITNS #NHST #OpenScience #Teaching #TheNewStatistics

#statstab #463 One-and-a-half sided test

Thoughts: Alberson has a more different take on the issues from #461 and #462: human behaviour.

(excerpt from the book)

#pvalue #onesided #NHST #directional #hypothesis #testing #logic

https://www.routledge.com/Statistics-As-Principled-Argument/Abelson/p/book/9780805805284