Rethinking Rob Kass’ recent talk on science in a less statistics-centric way.
Reflection on a recent post on a talk by Rob Kass’ has lead me to write this post. I liked the talk very much and found it informative. Perhaps especially for it’s call to clearly distinguish abstract models from brute force reality. I believe that is a very important point that has often been lost sight of by many statisticians in the past. I would actually point to many indicating Box’s quote “all models are wrong, but some...
Some possibly different experiences of being a statistician working with an international collaborative research group like OHDSI.
This post is by Keith O’Rourke and as with all posts and comments on this blog, is just a deliberation on dealing with uncertainties in scientific inquiry and should not to be attributed to any entity other than the...
Somethings do not seem to spread easily – the role of simulation in statistical practice and perhaps theory.
Unlike Covid19, somethings don’t seem to spread easily and the role of simulation in statistical practice (and perhaps theory) may well be one of those. In a recent comment, Andrew provided a link to an interview...
Somethings do not spread easily and are prone to dying out – the role of simulation in statistical practice and perhaps theory.
Unlike the Covid19, somethings don’t seem to spread easily and the role of simulation in statistical practice and perhaps theory may well be one of those. In a recent comment, Andrew provided a link to an interview...
Usual channels of clinical research dissemination getting somewhat clogged: What can go wrong – does.
A few weeks ago I was an observer on the OHDSI Covid19 study-a-thon (March 26 – 29). Four days of intensive collaboration among numerous clinical researchers working with previously established technology to enable high quality research with data access up to 500 million patients. Current status here. This is a good summary of what happened: “I am extremely proud to see what our community accomplished, but we are well aware that...
Update: OHDSI COVID-19 study-a-thon.
Thought a summary in the read below section might be helpful as the main page might be a lot to digest. The OHDSI Covid 19 group re-convenes at 6:00 (EST I think) Monday for updates. For those who want to do modelling, you cannot get the data but must write analysis scripts that data holders will run on their computers and return results. My guess is that might be most doable through here where custom R scripts can be implemented that...
And the band played on: Low quality studies being published on Covid19 prediction.
According to Laure Wynants et al Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection most of the recent published studies on prediction of Covid19 are of rather low quality. Information is desperately needed but not misleading information :-( Conclusion: COVID-19 related prediction models for diagnosis and prognosis are quickly entering the academic literature through...
OHDSI COVID-19 study-a-thon.
The OHDSI COVID-19 study-a-thon started early on Thursday morning – 3 am for me. The wrap up session – of the START of the Odyssey that needs to continue – will be available at 7 pm eastern time / EDT. This will give anyone who might be able to contribute to a world wide collaboration to enable better decision making and research on Covid19 a sense about what has happened so far. I’ll add the link when I get it or anyone...
We need to practice our best science hygiene.
Of course I am not referring to hand-washing and social distancing but rather heightened social interactions between those now engaged or who can get engaged in trying to get less wrong about Covid19. That is, being open about one’s intentions (the purpose of the effort), one’s methods and one’s data and data sources. For instance these data sources, Canada testing and results, US testing and results and some information on...
Attempts at providing helpful explanations of statistics must avoid instilling misleading or harmful notions: ‘Statistical significance just tells us whether or not something definitely does or definitely doesn’t cause cancer’
This post is by Keith O’Rourke and as with all posts and comments on this blog, is just a deliberation on dealing with uncertainties in scientific inquiry and should not to be attributed to any entity other than the...
Zombie semantics spread in the hope of keeping most on the same low road you are comfortable with now: Delaying the hardship of learning better methodology.
Now, everything is connected, but this is not primarily about persistent research misconceptions such as statistical significance. Instead it is about (inherently) interpretable ML versus (misleading with some nonzero...
Filling/emptying the half empty/full glass of profitable science: Different views on retiring versus retaining thresholds for statistical significance.
Unless you are new to this blog, you likely will know what this is about. Now, by profitable science in the title is meant repeatedly producing logically good explanations which “through subjection to the test of...
The virtue of fake universes: A purposeful and safe way to explain empirical inference.
I keep being drawn to thinking there is a away to explain statistical reasoning to others that will actually do more good than harm. Now, I also keep thinking I should know better – but can’t stop. My recent attempt starts with a shadow metaphor, then a review of analytical chemistry and moves to the concept of abstract fake universes (AFUs). AFU’s allow you to be the god of a universe, though not a real one ;-). However, ones...
Brief summary notes on Statistical Thinking for enabling better review of clinical trials.
This post is not by Andrew. Now it was spurred by Andrew’s recent post on Statistical Thinking enabling good science. The day of that post, I happened to look in my email’s trash and noticed that it went back to...
To better enable others to avoid being misled when trying to learn from observations, I promise not be transparent, open, sincere nor honest?
I recently read a paper by Stephen John with the title “Epistemic trust and the ethics of science communication: against transparency, openness, sincerity and honesty”. On a superficial level, John’s paper can be...
Is it possible to paint an overly bleak picture of university based clinical research?
Recently I was reminiscing with an old colleague about how our publications from almost 30 years ago that tried to encourage better conduct and reporting of clinical research seemed to have had so little impact. This...
What I missed on fixed effects (plural).
In my [Keith] previous post that criticised a publish paper, the first author commented they wanted some time to respond and I agreed. I also suggested that if the response came in after most readers have moved on I would re-post their response as a new post pointing back to the previous. So here we are. Now there has been a lot of discussion on this blog about public versus private criticism and their cost and benefit trade offs. One...
What am I missing and what will this paper likely lead researchers to think and do?
This post is by Keith. In a previous post Ken Rice brought our attention to a recent paper he had published with Julian Higgins and Thomas Lumley (RHL). After I obtained access and read the paper, I made some critical comments regarding RHL which ended with “Or maybe I missed something.” This post will try to discern what I might have missed by my recasting some of the arguments I discerned as being given in the paper. I do...