Large Deviation Theory (LDT):
LDT provides the asymptotic rate at which the probability of rare events decays exponentially. It quantifies how quickly improbable events (e.g., an unusually high number of errors in data transmission) become vanishingly small. It's crucial for…
It’s interesting that abandoning p-values and false discovery rates for 2nd generation p-values results in major reductions in decision errors: journals.plos.org/plosone/articl…
#Statistics thought of the day: To the entire non-statistical world, 'error' means 'mistake' but not in frequentism. Type I assertion probability α isn't P(mistake in asserting θ>0), i.e., P(θ <= 0 | p < 0.05); the assertion is made without knowing θ. hbiostat.org/bbr/alpha
When thinking about causal inference, mechanistic or process models are important. I think that the association of “causal” with black-box models leads to lots of problems.
statmodeling.stat.columbia.edu/2025/09/19/whe…
メディケアの薬価交渉にQALY使わないため、代替指標3つの解説✍
・Equalvalue of life years (evLY)
・Health years in total (HYT)
・Generalized risk-adjusted cost-effectiveness (GRACE)
Perspectives from the Healthcare Economist: CMS doesn’t consider QALYs becarispublishing.com/digital-conten…
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An epidemiologist, working for the National Cancer Center, Japan
Working for The Journal of Epidemiology as well
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