🖥️ This project is 100% computational, offering you the chance to refine your skills in #Statistics and #CausalInference. You’ll adapt surrogate endpoint methods to longitudinal data - this could transform observational clinical research! #DataScience [3/4]
November 10, 2025 at 9:49 PM
🖥️ This project is 100% computational, offering you the chance to refine your skills in #Statistics and #CausalInference. You’ll adapt surrogate endpoint methods to longitudinal data - this could transform observational clinical research! #DataScience [3/4]
#statstab #456 Shall we count the living or the dead?
Thoughts: survival ratio -> if the intervention increases risk of the outcome
risk ratio -> if the intervention reduces risk of the outcome
#causalinference #riskratios #survivalanalysis #estimand
arxiv.org/abs/2106.063...
Thoughts: survival ratio -> if the intervention increases risk of the outcome
risk ratio -> if the intervention reduces risk of the outcome
#causalinference #riskratios #survivalanalysis #estimand
arxiv.org/abs/2106.063...
Shall we count the living or the dead?
In the 1958 paper "Shall we count the living or the dead?", Mindel C. Sheps proposed a principled solution to the familiar problem of asymmetry of the relative risk. We provide causal models to clarif...
arxiv.org
November 10, 2025 at 7:01 PM
#statstab #456 Shall we count the living or the dead?
Thoughts: survival ratio -> if the intervention increases risk of the outcome
risk ratio -> if the intervention reduces risk of the outcome
#causalinference #riskratios #survivalanalysis #estimand
arxiv.org/abs/2106.063...
Thoughts: survival ratio -> if the intervention increases risk of the outcome
risk ratio -> if the intervention reduces risk of the outcome
#causalinference #riskratios #survivalanalysis #estimand
arxiv.org/abs/2106.063...
In the future, improved causal inference methods could enable AI systems to make better decisions, personalize treatments, and understand complex systems more deeply—transforming everyday life and scientific discovery. #DataScience #CausalInference
November 10, 2025 at 6:53 AM
In the future, improved causal inference methods could enable AI systems to make better decisions, personalize treatments, and understand complex systems more deeply—transforming everyday life and scientific discovery. #DataScience #CausalInference
"Association does not imply causation" is the truth and continues to be an important mantra in the practice of statistics. What does it actually mean? Can we prove causal relationships using observational data? If no, does it mean that detected associations are useless? #statssky #causalinference
November 8, 2025 at 4:02 PM
"Association does not imply causation" is the truth and continues to be an important mantra in the practice of statistics. What does it actually mean? Can we prove causal relationships using observational data? If no, does it mean that detected associations are useless? #statssky #causalinference
This MR study assessed causal links between thousands of plasma proteins and epilepsy risk.
doi.org/10.1002/epi4...
#epilepsy #ILAE #epilepsiaopen #causalinference #GWAS #MR #plasmaproteins
doi.org/10.1002/epi4...
#epilepsy #ILAE #epilepsiaopen #causalinference #GWAS #MR #plasmaproteins
November 5, 2025 at 2:56 PM
This MR study assessed causal links between thousands of plasma proteins and epilepsy risk.
doi.org/10.1002/epi4...
#epilepsy #ILAE #epilepsiaopen #causalinference #GWAS #MR #plasmaproteins
doi.org/10.1002/epi4...
#epilepsy #ILAE #epilepsiaopen #causalinference #GWAS #MR #plasmaproteins
Follow along this month as @harvardepi.bsky.social spotlights the CAUSALab team! 👇 #causalinference #epidemiology
This month, we are featuring @causalab.bsky.social as the final installment in our '25 series spotlighting our research groups.
Launched in '21, by @miguelhernan.org, CAUSALab uses data to investigate what works in medicine, public health & policy.
Follow along to learn more about #causalinference
Launched in '21, by @miguelhernan.org, CAUSALab uses data to investigate what works in medicine, public health & policy.
Follow along to learn more about #causalinference
November 5, 2025 at 1:47 PM
Follow along this month as @harvardepi.bsky.social spotlights the CAUSALab team! 👇 #causalinference #epidemiology
This month, we are featuring @causalab.bsky.social as the final installment in our '25 series spotlighting our research groups.
Launched in '21, by @miguelhernan.org, CAUSALab uses data to investigate what works in medicine, public health & policy.
Follow along to learn more about #causalinference
Launched in '21, by @miguelhernan.org, CAUSALab uses data to investigate what works in medicine, public health & policy.
Follow along to learn more about #causalinference
November 4, 2025 at 7:37 PM
This month, we are featuring @causalab.bsky.social as the final installment in our '25 series spotlighting our research groups.
Launched in '21, by @miguelhernan.org, CAUSALab uses data to investigate what works in medicine, public health & policy.
Follow along to learn more about #causalinference
Launched in '21, by @miguelhernan.org, CAUSALab uses data to investigate what works in medicine, public health & policy.
Follow along to learn more about #causalinference
ML wealth maps from space 🛰️ are great, but suffer from "shrinkage" bias, which waters down policy impact results (causal inference). We developed correction methods that fix this bias *without* new data.
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
November 4, 2025 at 1:30 PM
ML wealth maps from space 🛰️ are great, but suffer from "shrinkage" bias, which waters down policy impact results (causal inference). We developed correction methods that fix this bias *without* new data.
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
arxiv.org/abs/2508.01341
#CausalInference #DataForGood #AI #PovertyMapping #EarthObservation
New Instats livestreaming seminar: Causal AI for Real-World Data
#Biostatistics #CausalInference #DataAnalytics #Epidemiology #HealthEconomics #MachineLearning #PublicHealth #Statistics #DataScience #ComputerScience #Python #R #Research #ResearchTraining #Instats
#Biostatistics #CausalInference #DataAnalytics #Epidemiology #HealthEconomics #MachineLearning #PublicHealth #Statistics #DataScience #ComputerScience #Python #R #Research #ResearchTraining #Instats
Causal AI for Real-World Data - Livestream starting Jan 19, 2026 (UTC)
Join Andy Wilson (Spencer Fox Eccles School of Medicine, Univ. of Utah) for a one-day, hands-on workshop applying the Causal Roadmap to turn observational health data into defensible causal answers — ideal for PhD students, faculty, and researchers in biostatistics, epidemiology, health economics, ML and related fields. Through live DAG construction, causal discovery (gCastle/Python), estimation labs in R (propensity methods, g-computation, TMLE with SuperLearner, DML), and generative validation (VAE-based simulations), you’ll practice end-to-end target-trial emulation and leave with reproducible artifacts (DAGs, adjustment sets, R/Python scripts, comparison plots) and a practical toolkit for designing, estimating, and defending causal analyses. The highly interactive format combines short lectures, group work, and guided coding — recordings and all materials are available for 30 days after the seminar, and participants receive a certificate of completion. Register to build transferable technical skills that will strengthen your dissertation, method development, or applied research and help your analyses stand up to peer review and regulatory scrutiny.
#Biostatistics #CausalInference #DataAnalytics #Epidemiology #HealthEconomics #MachineLearning #PublicHealth #Statistics #DataScience #ComputerScience #Python #R #Research #ResearchTraining #Instats
instats.org
November 2, 2025 at 4:21 PM
New Instats livestreaming seminar: Causal AI for Real-World Data
#Biostatistics #CausalInference #DataAnalytics #Epidemiology #HealthEconomics #MachineLearning #PublicHealth #Statistics #DataScience #ComputerScience #Python #R #Research #ResearchTraining #Instats
#Biostatistics #CausalInference #DataAnalytics #Epidemiology #HealthEconomics #MachineLearning #PublicHealth #Statistics #DataScience #ComputerScience #Python #R #Research #ResearchTraining #Instats
New paper on causal inference for urban ecology & evolution, with a primer on DAGs & a case study on squirrel coat color. 🏙️➡️🐿️ Check it out: rdcu.be/eNz0O #CausalInference #UrbanEcoEvo
Beyond urbanization metrics: Using graphical causal models to investigate mechanisms in urban ecology and evolution
rdcu.be
October 31, 2025 at 5:07 PM
New paper on causal inference for urban ecology & evolution, with a primer on DAGs & a case study on squirrel coat color. 🏙️➡️🐿️ Check it out: rdcu.be/eNz0O #CausalInference #UrbanEcoEvo
Measuring how brand awareness or reach drives business results is tough.
The new notebook in PyMC-Marketing v0.17.0 uses causal reasoning + joint models to connect upper-funnel efforts to real outcomes.
🧩𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯: dub.link/sOQNdUp
#MarketingAnalytics #CausalInference #PyMC #OpenSource
The new notebook in PyMC-Marketing v0.17.0 uses causal reasoning + joint models to connect upper-funnel efforts to real outcomes.
🧩𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯: dub.link/sOQNdUp
#MarketingAnalytics #CausalInference #PyMC #OpenSource
October 30, 2025 at 1:12 PM
Measuring how brand awareness or reach drives business results is tough.
The new notebook in PyMC-Marketing v0.17.0 uses causal reasoning + joint models to connect upper-funnel efforts to real outcomes.
🧩𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯: dub.link/sOQNdUp
#MarketingAnalytics #CausalInference #PyMC #OpenSource
The new notebook in PyMC-Marketing v0.17.0 uses causal reasoning + joint models to connect upper-funnel efforts to real outcomes.
🧩𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯: dub.link/sOQNdUp
#MarketingAnalytics #CausalInference #PyMC #OpenSource
Save the dates! 📌
CAUSALab's Summer Courses on Causal Inference return June 2026. Course information and registration details to be announced in the coming weeks.
Join our 2025-2026 listserv to receive updates first:
harvard.az1.qualtrics.com/jfe/form/SV_... #causalinference #epidemiology
CAUSALab's Summer Courses on Causal Inference return June 2026. Course information and registration details to be announced in the coming weeks.
Join our 2025-2026 listserv to receive updates first:
harvard.az1.qualtrics.com/jfe/form/SV_... #causalinference #epidemiology
October 29, 2025 at 7:18 PM
Save the dates! 📌
CAUSALab's Summer Courses on Causal Inference return June 2026. Course information and registration details to be announced in the coming weeks.
Join our 2025-2026 listserv to receive updates first:
harvard.az1.qualtrics.com/jfe/form/SV_... #causalinference #epidemiology
CAUSALab's Summer Courses on Causal Inference return June 2026. Course information and registration details to be announced in the coming weeks.
Join our 2025-2026 listserv to receive updates first:
harvard.az1.qualtrics.com/jfe/form/SV_... #causalinference #epidemiology
Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.
Evaluating AI and Machine Learning Algorithms for Causal Inference | Online Seminar | Statistical Horizons
This online Distinguished Speaker course by Kosuke Imai, Ph.D., introduces causal inference frameworks for evaluating AI and machine learning algorithms.
statisticalhorizons.com
October 28, 2025 at 1:43 PM
Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.
Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.
Evaluating AI and Machine Learning Algorithms for Causal Inference | Online Seminar | Statistical Horizons
This online Distinguished Speaker course by Kosuke Imai, Ph.D., introduces causal inference frameworks for evaluating AI and machine learning algorithms.
statisticalhorizons.com
October 28, 2025 at 1:41 PM
Distinguished Speaker Kosuke Imai presents "Evaluating AI & Machine Learning Algorithms for #causalinference", Feb. 10. Learn to assess #AI & #machinelearning practically—from heterogeneous treatment effects, individualized treatment rules, & human–AI collaboration.
#statstab #446 {causaldata} Packages of Example Data for The Effect
Thoughts: On your journey to learning Causal Inference you can use some nice datasets to figure out how horrible it can all go.
#causalinference #observational #python #r #DAG #OS
github.com/NickCH-K/cau...
Thoughts: On your journey to learning Causal Inference you can use some nice datasets to figure out how horrible it can all go.
#causalinference #observational #python #r #DAG #OS
github.com/NickCH-K/cau...
GitHub - NickCH-K/causaldata: Packages of Example Data for The Effect
Packages of Example Data for The Effect. Contribute to NickCH-K/causaldata development by creating an account on GitHub.
github.com
October 27, 2025 at 5:33 PM
#statstab #446 {causaldata} Packages of Example Data for The Effect
Thoughts: On your journey to learning Causal Inference you can use some nice datasets to figure out how horrible it can all go.
#causalinference #observational #python #r #DAG #OS
github.com/NickCH-K/cau...
Thoughts: On your journey to learning Causal Inference you can use some nice datasets to figure out how horrible it can all go.
#causalinference #observational #python #r #DAG #OS
github.com/NickCH-K/cau...
This paper’s been popping as “evidence” that you can’t do real #causalinference w/ obs data. To me it shows you need rigorous pre-specified design (in addition to the willingness to fold when your hypothesis is not possible to answer with the data at hand). #EpiSky, #CausalSky, #AcademicSky
October 22, 2025 at 2:59 PM
This paper’s been popping as “evidence” that you can’t do real #causalinference w/ obs data. To me it shows you need rigorous pre-specified design (in addition to the willingness to fold when your hypothesis is not possible to answer with the data at hand). #EpiSky, #CausalSky, #AcademicSky
“Correlation is causation” 😈
New #substack going over the maths of correlation, t-test, and linear models. open.substack.com/pub/mzlotean...
#correlation #causalinference #effects #pearson #ttest
New #substack going over the maths of correlation, t-test, and linear models. open.substack.com/pub/mzlotean...
#correlation #causalinference #effects #pearson #ttest
Correlation *is* causation!
- at least mathematically
open.substack.com
October 22, 2025 at 10:47 AM
“Correlation is causation” 😈
New #substack going over the maths of correlation, t-test, and linear models. open.substack.com/pub/mzlotean...
#correlation #causalinference #effects #pearson #ttest
New #substack going over the maths of correlation, t-test, and linear models. open.substack.com/pub/mzlotean...
#correlation #causalinference #effects #pearson #ttest
Join our team as a 12-month PhD intern @ Roche (Basel)! 🧠
Project: Use causal inference & ML on proteomics to find causal drivers of Alzheimer's.
For: 3rd-year PhD candidates #Genomics #MachineLearning #CausalInference #CompBio #Alzheimers See details & apply here ➡️ t.co/zMuVjyMW26
Project: Use causal inference & ML on proteomics to find causal drivers of Alzheimer's.
For: 3rd-year PhD candidates #Genomics #MachineLearning #CausalInference #CompBio #Alzheimers See details & apply here ➡️ t.co/zMuVjyMW26
October 21, 2025 at 4:57 PM
Join our team as a 12-month PhD intern @ Roche (Basel)! 🧠
Project: Use causal inference & ML on proteomics to find causal drivers of Alzheimer's.
For: 3rd-year PhD candidates #Genomics #MachineLearning #CausalInference #CompBio #Alzheimers See details & apply here ➡️ t.co/zMuVjyMW26
Project: Use causal inference & ML on proteomics to find causal drivers of Alzheimer's.
For: 3rd-year PhD candidates #Genomics #MachineLearning #CausalInference #CompBio #Alzheimers See details & apply here ➡️ t.co/zMuVjyMW26
Clinical decision making in mental health 🧠
Alejandro Szmulewicz @hsph.harvard.edu continues the Methods Series @ki.se in 2 weeks.
📆 Nov 4, 2025
⏰ 15.00 CET/9.00 ET
📍 Online
Attend online:
stats.sender.net/forms/e7JD1d...
#causalinference #epidemiology
Alejandro Szmulewicz @hsph.harvard.edu continues the Methods Series @ki.se in 2 weeks.
📆 Nov 4, 2025
⏰ 15.00 CET/9.00 ET
📍 Online
Attend online:
stats.sender.net/forms/e7JD1d...
#causalinference #epidemiology
October 21, 2025 at 3:14 PM
Clinical decision making in mental health 🧠
Alejandro Szmulewicz @hsph.harvard.edu continues the Methods Series @ki.se in 2 weeks.
📆 Nov 4, 2025
⏰ 15.00 CET/9.00 ET
📍 Online
Attend online:
stats.sender.net/forms/e7JD1d...
#causalinference #epidemiology
Alejandro Szmulewicz @hsph.harvard.edu continues the Methods Series @ki.se in 2 weeks.
📆 Nov 4, 2025
⏰ 15.00 CET/9.00 ET
📍 Online
Attend online:
stats.sender.net/forms/e7JD1d...
#causalinference #epidemiology
Correlation isn’t causation, as the mantra goes—but statistical noise in correlational data can reveal causal information. When X and Y are causally linked, their noise tends to be asymmetric & this can guide #CausalInference. Check out our 📃👇 doi.org/10.1111/nous... #philsky #philsci #StatsSky #HPS
October 21, 2025 at 9:20 AM
Correlation isn’t causation, as the mantra goes—but statistical noise in correlational data can reveal causal information. When X and Y are causally linked, their noise tends to be asymmetric & this can guide #CausalInference. Check out our 📃👇 doi.org/10.1111/nous... #philsky #philsci #StatsSky #HPS
#statstab #440 Computing Statistical Power for the Difference in Differences Design
Thoughts: DiD studies are all the rage in Obs research. But how does the concept of power apply to them?
#poweranalysis #DiD #causalinference #samplesize #observational
journals.sagepub.com/doi/10.1177/...
Thoughts: DiD studies are all the rage in Obs research. But how does the concept of power apply to them?
#poweranalysis #DiD #causalinference #samplesize #observational
journals.sagepub.com/doi/10.1177/...
Sage Journals: Discover world-class research
Subscription and open access journals from Sage, the world's leading independent academic publisher.
journals.sagepub.com
October 17, 2025 at 7:20 PM
#statstab #440 Computing Statistical Power for the Difference in Differences Design
Thoughts: DiD studies are all the rage in Obs research. But how does the concept of power apply to them?
#poweranalysis #DiD #causalinference #samplesize #observational
journals.sagepub.com/doi/10.1177/...
Thoughts: DiD studies are all the rage in Obs research. But how does the concept of power apply to them?
#poweranalysis #DiD #causalinference #samplesize #observational
journals.sagepub.com/doi/10.1177/...
Hello Bluesky!
We rate DAGs. Some are great. Some are... not so great. But we rate them all.
Let's start with a famous powerpoint hairball a.k.a. "the Afghanisdag", presented to Gen. Stanley A. McChrystal around 2010. His own rating?
1/10 "When we understand that slide, we'll have won the war"
We rate DAGs. Some are great. Some are... not so great. But we rate them all.
Let's start with a famous powerpoint hairball a.k.a. "the Afghanisdag", presented to Gen. Stanley A. McChrystal around 2010. His own rating?
1/10 "When we understand that slide, we'll have won the war"
October 17, 2025 at 12:07 PM
Join us in London for an interactive and practical introduction to modern causal inference methods — with vegan and gluten-free refreshments included.
More info & registration 👉 www.ucl.ac.uk/brain-scienc...
#Epidemiology #CausalInference #UCL #ShortCourses
More info & registration 👉 www.ucl.ac.uk/brain-scienc...
#Epidemiology #CausalInference #UCL #ShortCourses
Causal Inference in Practice Short Course
This course covers the latest developments in causal inference methods and provides practical explanations for applying them to real research questions.
www.ucl.ac.uk
October 13, 2025 at 2:03 PM
Join us in London for an interactive and practical introduction to modern causal inference methods — with vegan and gluten-free refreshments included.
More info & registration 👉 www.ucl.ac.uk/brain-scienc...
#Epidemiology #CausalInference #UCL #ShortCourses
More info & registration 👉 www.ucl.ac.uk/brain-scienc...
#Epidemiology #CausalInference #UCL #ShortCourses
📢 Registration is open for Causal Inference in Practice — a 3-day short course at UCL
🗓️ 18–20 February 2026
Taught by me, @kdiazordaz.bsky.social & Peter Martin.
Learn to estimate causal effects from observational data.
👉 www.ucl.ac.uk/brain-scienc...
#CausalInference #Epidemiology #DataScience
🗓️ 18–20 February 2026
Taught by me, @kdiazordaz.bsky.social & Peter Martin.
Learn to estimate causal effects from observational data.
👉 www.ucl.ac.uk/brain-scienc...
#CausalInference #Epidemiology #DataScience
Causal Inference in Practice Short Course
This course covers the latest developments in causal inference methods and provides practical explanations for applying them to real research questions.
www.ucl.ac.uk
October 13, 2025 at 2:03 PM
📢 Registration is open for Causal Inference in Practice — a 3-day short course at UCL
🗓️ 18–20 February 2026
Taught by me, @kdiazordaz.bsky.social & Peter Martin.
Learn to estimate causal effects from observational data.
👉 www.ucl.ac.uk/brain-scienc...
#CausalInference #Epidemiology #DataScience
🗓️ 18–20 February 2026
Taught by me, @kdiazordaz.bsky.social & Peter Martin.
Learn to estimate causal effects from observational data.
👉 www.ucl.ac.uk/brain-scienc...
#CausalInference #Epidemiology #DataScience
Participants include Vanderbilt Biostatistics PhD students Hannah Klinger and @ashleymullan.bsky.social, professor Rameela Raman, and alumni Sarah Lotspeich, Lucy McGowan, and Jacquelyn Neal. www.vanderbilt.edu/biostatistic... #CausalInference #StudentResearch #PublicHealth
October 13, 2025 at 5:11 AM
Participants include Vanderbilt Biostatistics PhD students Hannah Klinger and @ashleymullan.bsky.social, professor Rameela Raman, and alumni Sarah Lotspeich, Lucy McGowan, and Jacquelyn Neal. www.vanderbilt.edu/biostatistic... #CausalInference #StudentResearch #PublicHealth