Michael Plank
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michaelplanknz.bsky.social
Michael Plank
@michaelplanknz.bsky.social
2.6K followers 1.7K following 1K posts
Professor of Applied Mathematics at the University of Canterbury, NZ. Fellow @royalsocietynz.bsky.social. Math modelling in biology and epidemiology. Bicycles make the world a better place. He/him
https://www.math.canterbury.ac.nz/~m.plank/
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Reposted by Michael Plank
adamjkucharski.bsky.social
I wrote more previously about the evidence base around MMR and vaccination, and why people need to make *testable* hypotheses, rather than slipperly claims that endlessly evolve after being falisified... kucharski.substack.com/p/a-wild-vac...
November 20, 2025 at 9:58 AM
Reposted by Michael Plank
bbolker.bsky.social
Does everyone know about this one already? Meng 2018. “Statistical Paradises and Paradoxes in Big Data ...” Annals of Applied Statistics doi.org/10.1214/18-A...
Statisticians are increasingly posed with thought-provoking and even paradoxical questions, challenging our qualifications for entering the statistical paradises created by Big Data. By developing measures for data quality, this article suggests a framework to address such a question: “Which one should I trust more: a 1% survey with 60% response rate or a self-reported administrative dataset covering 80% of the population?” A 5-element Eulerformula-like identity shows that for any dataset of size n, probabilistic or not, the difference between the sample average Xn and the population average XN is the product of three terms: (1) a data quality measure, ρR,X, the correlation between Xj and the response/recording indicator Rj ; (2) a data quantity measure, √(N − n)/n, where N is the population size; and (3) a problem difficulty measure, σX, the standard deviation of X. This decomposition provides multiple insights: (I) Probabilistic sampling ensures high data quality by controlling ρR,X at the level of N −1/2; (II) When we lose this control, the impact of N is no longer canceled by ρR,X, leading to a Law of Large Populations (LLP), that is, our estimation error, relative to the benchmarking rate 1/√n, increases with √N; and (III) the “bigness” of such Big Data (for population inferences) should be measured by the relative size f = n/N , not the absolute size n; (IV) When combining data sources for population inferences, those relatively tiny but higher quality ones should be given far more weights than suggested by their sizes.
November 19, 2025 at 4:57 PM
michaelplanknz.bsky.social
Yes indeed
November 18, 2025 at 8:01 AM
michaelplanknz.bsky.social
Woah is that jump from 2023 -> 24 the scrapping of the clean car discount? 😮
November 17, 2025 at 8:01 AM
michaelplanknz.bsky.social
I saw this and it made me think maybe the spike is reflecting increase in domestic violence, which I think was seen in other countries too (but in the US tends to involve firearms more than elsewhere)

bsky.app/profile/mega...
meganranney.bsky.social Megan Ranney MD MPH @meganranney.bsky.social · 13d
New paper reminds us yet again: HOMICIDE is the leading cause of death for pregnant women.

Gun violence & partner violence are related.

All-cause homicide & firearm homicide of pregnant women are higher, in states w/ higher calculated firearm ownership (1/x 🧵

jamanetwork.com/journals/jam...
Firearm Homicide in Pregnant Women and State-Level Firearm Ownership
This cross-sectional study examines firearm homicide rates in pregnant compared with nonpregnant women and whether estimated state-level firearm ownership is associated with homicide deaths among preg...
jamanetwork.com
November 17, 2025 at 7:41 AM