“On the Birnbaum Argument for the Strong Likelihood Principle”, in Statistical Science 2014

https://www.phil.vt.edu/dmayo/personal_website/mayo_statsci_published-birnbaum_argument_for_slp_-commentary__rejoinder.pdf

is a fantastic contribution to statistical inference.

Cheers,

Justin

http://www.statisticool.com

Mayo has spent four decades telling people how statistical inference must surely be done. Written entire books telling people how to do it. Invented new methods to do it. Argued endlessly about it. Maintained a fanatical anti-Bayesianism the entire time. I can’t even remember how many times I’ve seen someone point out (with details, demonstrations, and evidence) errors in her reasoning and she never changed her mind on anything or admit the slightest mistake. She’s that certain she’s got the goods on “statistical inference”.

Ok. Let’s see *her* perform, with *her* ideas, real statistical inference on a non trivial example where the answer isn’t known or obvious ahead of time. Let’s see what her powerful insights and philosophical genius can actually do.

]]>So….you also think Mayo’s never going use her ideas for a single real statistical inference either?

]]>Luckily we have the recent post about the golf putting model which makes the point in some detail:

https://statmodeling.stat.columbia.edu/2019/10/04/golf-example-now-a-stan-case-study/

This is not just a random sampling from an RNG model + some kind of prior, this is the development of some “physics”: consequences of geometry, dynamics, mathematics, and soforth incorporated mathematically into the expression of the relationship between one set of facts and another.

]]>Right, the point of Bayesian analysis isn’t to do basically the same analysis and get a slightly different answer with slightly different interpretation… It’s to enable sophisticated scientific analyses that involve generating processes that are much different from the kind used in typical frequentist analyses. Whether this data set can be used in such a manner is a different, subject matter specific question. You can’t just bolt on Bayes, you have to use Bayes to enable subject matter specific inquiry.

]]>This would actually be a better opportunity to demonstrate how one would do a Bayesian analysis here because none of the original or current papers use any Bayesian techniques.

You need to go far beyond “bayesian analysis” to do something useful with this data. Just replacing the arbitrarily valued coefficient of a Frequentist model with an arbitrarily valued coefficient of a Bayesian model is not going to help you.

The p = 10^-74 was based on one set of features, and the p > 0.05 on another set of features. No surprise that it changes since it is just the arbitrary number chosen to optimizes the fit of the model…

]]>This would actually be a better opportunity to demonstrate how one would do a Bayesian analysis here because none of the original or current papers use any Bayesian techniques.

We read “effect size estimates released from their 2015 study were strongly affected by population structure due to a computational bug”. If Bayesian analyses were used, the same thing could have happened something like: “New data shows the Bayes factor went from 137 to 3”.

The newer papers mention structure as a confounder, but in the Field paper (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5182071/), regarding the 10^-74 p-value, they write:

“This is not an artifact of uncontrolled population structure in the GWAS, as the correlation is even stronger for a smaller family-based GWAS that provides stringent structure control”

Speaking about effects of other traits, the Field paper writes:

“Although these signals are highly intriguing, and some match known phenotypes of modern Britons, the confounding role—if any—of population structure in contributing to these signals remains to be fully determined.”

The new paper says “The slope is ~1/3 as large as in GIANT, though still modestly significant (p = 1.2 x 10^-2)”.

IMO things are still a bit murky. No one doubts the phenomena, just the strength of the effect.

I’d like to see Field’s team followup.

Cheers,

Justin

http://www.statisticool.com

Paul:

Off topic but I agree that these are both interesting.

]]>https://en.wiktionary.org/wiki/sibling

“1903, modern revival of Old English sibling (“relative, a relation, kinsman”), equivalent to sib + -ling. Compare Middle English sib, sibbe (“relative; kinsman”), German Sippe. The term apparently meant merely kin or relative until the 20th century when its necessity for the study of genetics led to its specialized use. For example, the OED has a 1903 citation in which “sibling” must be defined for those who don’t know the intended meaning [!].”

In other words, until 1903, the English language lacked a word to designate “brother or sister.” One would of thought the word goes back to antiquity. Likewise, the term “antisemitism” is not much older than “sibling.” From https://en.wiktionary.org/wiki/anti-Semitism

“[antisemitism] was coined in 1879 by German political agitator Wilhelm Marr to replace Judenhaß (“Jew-hatred”) to make hatred of the Jews seem rational and sanctioned by scientific knowledge. The similar term antisemitisch (“anti-semitic”) was first used in 1860”

]]>Ha Ha

]]>I Boz-ywood perhaps.

]]>Or maybe even around to world to Bollywood!

]]>Yes, I’m sure we’d all really like to get the LOWDOWN on the Scaggs phenomenon. If we don’t figure this out, there could be a BREAKDOWN DEAD AHEAD. WHAT CAN I SAY? This may well be one of the most important questions we have across the whole country from GEORGIA to HOLLYWOOD.

]]>I’m sure that there are SNPs associated with being named “Skaggs.” The only question is whether those SNPs cause people to name their children Skaggs or causes women to marry men named Skaggs. I hope a study on this question is receiving a lot of funding.

]]>“the argument that if something looks salient, it must be adaptive, has a very weak footing. Unfortunately, this argument is used axiomatically in evolutionary psychology.”

+1

]]>In certain cities in Kentucky, there are far more people with the name “Skaggs” than in other cities. The anomaly is far too large to have occurred due to chance, so the only reasonable conclusion is that we Skaggs are genetically superior to other residents of Kentucky.

Sarcasm aside, the argument that if something looks salient, it must be adaptive, has a very weak footing. Unfortunately, this argument is used axiomatically in evolutionary psychology.

]]>This would be a perfect opportunity for Mayo to demonstrate the potential of her SEV function.

]]>