Paul Feyerabend, Against Method.
Prescriptions about how science MUST be done? Simply a bad, authoritarian idea. And based on the history of science, not good for scientific progress.
#metasci
I don’t know if ”all unhappy families are unhappy in their own way,” is true or not, but *in book that the quote is from* all the unhappy families are, in fact, unhappy in the same way. Namely they got married too fast, and now they’re stuck with an incompatible spouse.
Ok so if 2,300 people from #Sweden and then another 160,000 #EU citizens sign this it will have reached the threshold of a million signatures and 7 counties reaching the threshold.
But they have to sign it by tomorrow.... #Spéirgorm #Pride #LGBT
No one asked, but here’s my opinion of preregistration badges: They’e uninformtive! Preregistration is neither necessary nor sufficient for good science. A study can be bad and preregistered and it can be good and not preregistered. So what do we gain by knowing it was preregistered? Not much!
Finally downloaded Sekiro. V excited to play a from game where you only die twice.
Does microtargeting work? The idea that people can be manipulated by political messages that are furtively tailored to their personality or other vulnerabilities has triggered much concern. But how well founded are those concerns? 1/n
Hey friends and strangers Has anyone read a particularly great psychology phd thesis lately? I am beginning to write my phd thesis and it would be inspiring to read a great phd thesis.
FORMAL EPISTEMOLOGISTS: Interesting argument. However, I have already constructed a formal model on which you are the irrational soyjack and I am the rational chad
Everyone’s always talking about how we need more women in stem. You know who’s truly underrepresented in stem? Children. The true final frontier of stem. We need more children in stem.
Researchers often need to justify their choice of sample size, particularly in fields such as animal research, where there are obvious ethical concerns about relying on too many or too few study subjects. The common approach is still to depend on statistical power calculations, typically carried out using simple formulas and default values. Over-reliance on power, however, not only carries the baggage of statistical hypothesis tests that have been criticized for decades, but also blocks an opportunity to strengthen the research in the design phase by learning about challenges in interpretation before the study is carried out. We recommend constructing a “quantitative backdrop” in the planning stage of a study, which means explicitly connecting ranges of possible research outcomes to their expected real-life implications. Such a backdrop can then in principle serve to identify single values of interest for use in traditional power analyses; or better, inform sample size investigations based on the goal of achieving an interval width narrow enough to distinguish values deemed practically or clinically important from those not representing practically meaningful effects. The latter bases calculations on a desired precision (rather than desired power) and relies on meaningful context rather than estimates obtained from previous research. Sample size justification should not be seen as an automatic math exercise with a right answer, but as a nuanced a priori investigation of measurement, design, analysis, and interpretation challenges.
"Real-life error rates are unknown and even difficult to fully conceptualize....Theoretical error rates are only as trustworthy as the assumed model of the process that generated the real-life data."
New preprint by Megan Higgs and Valentin Amrhein: www.preprints.org/manuscript/2...
#Methodology 🧪
Modest proposal: instead of saying statistically significant, we used the term 'precisely measured'.
I think this communicates what the p value does add while also raising the question, ”that’s great, but how big is the effect?” ”
Desperately searching for participants for a cheese study. I can’t pay, you will have to do a fair amount of work and the potential upsides are dubious at best. Send me an email if you’re interested (if you are the kind of motivated participant I’m looking for, you’ll find it on your own).
There’s nothing sadder than an empty feed so here is a placeholder bleet (bluesky-tweet) until I think of something to say (which may never happen).
