#statstab #549 Nonrandomized studies using causal-modeling may give different answers than RCTs

Thoughts: "effect estimates deviated 1.58-fold between the study designs"

#Nof1 #randomization #causalinference #observational #marginalstructuralmodels

https://pubmed.ncbi.nlm.nih.gov/31704350/

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#statstab #529 Understanding and misunderstanding randomized controlled trials

Thoughts: Randomization is close to magic, but we still must be critical of our methods.

#randomization #rct #design #critique #covariates #causalinference #ATE #confounder #bias

https://doi.org/10.1016/j.socscimed.2017.12.005

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#statstab #511 Seven Myths of Randomisation
in Clinical Trials

Thoughts: Randomization is a very powerful tool for inference. Closest we have to magic in research. But it's also misunderstood.

#randomization #experiment #inference #design #bias #science

https://www.methodologyhubs.mrc.ac.uk/files/9214/3711/9501/Plenary-_Stephen_Senn.pdf

#statstab #458 There is still only one test

Thoughts: Downey make a good point that all/any testing ensemble does essentially the same thing.

#randomization #testing #nhst #pvalue

https://allendowney.blogspot.com/2016/06/there-is-still-only-one-test.html