iiinova — where your digital self keeps evolving

Miguel Hernan @miguelhernan.org · 02/04/2026

Two common misconceptions when repurposing data for #causalinference: 1) the target trial is an ideal trial 2) the target trial protocol can be prespecified Our new paper examines how the target trial protocol depends on the causal question AND the available data. journals.lww.com/epidem/abstr...

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Miguel Hernan @miguelhernan.org · 16/12/2025

New study: Small benefits and risks of COVID-19 vaccines in children in Madrid. Hospitalization risk very low in unvaccinated, lower in vaccinated. 6-11 years old: no myocarditis cases 12-17 years old: myocarditis risk very low in vaccinated, lower in unvaccinated journals.lww.com/pidj/fulltex...

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Miguel Hernan @miguelhernan.org · 18/02/2025

2/ The #TargetTrial framework is a structured procedure to operationalize good practices for study design, data analysis, and reporting. It avoids design-induced biases but not biases arising from data limitations, such as measurement error and insufficient information to adjust for confounding.

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Miguel Hernan @miguelhernan.org · 18/02/2025

1/ When using observational data for #causalinference, emulating a target trial helps solve some problems... but not all problems. In a new paper, we explain why and when the #TargetTrial framework is helpful. www.acpjournals.org/doi/10.7326/... Joint work with my colleagues @causalab.bsky.social

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Miguel Hernan @miguelhernan.org · 03/02/2025

1/ If you were taught to test for proportional hazards, talk to your teacher. The proportional hazards assumption is implausible in most #randomized and #observational studies because the hazard ratios aren't expected to be constant during the follow-up. So "testing" is futile. But there is more 👇

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Miguel Hernan @miguelhernan.org · 06/01/2025

2/ Immortal time may occur when individuals 1) are assigned to treatment strategies based on post-eligibility information or 2) determined to be eligible based on post-assignment information. #TargetTrial emulation prevents it by synchronizing eligibility and assignment at the start of follow-up.

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Miguel Hernan @miguelhernan.org · 06/01/2025

1/ That "immortal time" is so frequent in survival analyses for #causalinference is fascinating. Because "immortal time" doesn't exist in the data, *we* create it when misanalyzing the data. Our new paper pubmed.ncbi.nlm.nih.gov/39494894/ summarizes why immortal time arises & how to prevent it.

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Miguel Hernan @miguelhernan.org · 23/12/2024

Upgrade your #causalinference arsenal. A revision of our book "Causal Inference: What If" is available at miguelhernan.org/whatifbook Thanks to everyone who suggested improvements, reported typos, and proposed new citations and material. Enjoy the #WhatIfBook plus code and data. Also, it's free.

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Miguel Hernan @miguelhernan.org · 26/11/2024

Does #randomization ensures balance of risk factors between groups? Consider this: In Denmark 860 individuals were randomly allocated to either intervention or control. Individuals were unaware of their allocation. No intervention took place. Mortality was higher in the intervention group (p=0.003)

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Miguel Hernan @miguelhernan.org · 20/11/2024

It's always a good time to remember Brandolini's principle @ziobrando.bsky.social

Alberto Brandolini presents a slide with the text "The amount of energy necessary to refute bullshit is an order of magnitude bigger than to produce it"

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Miguel Hernan @miguelhernan.org · 23/06/2024

This week I discussed methods for health technology assessment at HTAi. My main point: "Observational data (#RWD) can often be used to emulate a #TargetTrial, but we need more research to characterize questions that can only be answered by randomized trials." Let's learn the limits of #RWE.

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Miguel Hernan @miguelhernan.org · 11/06/2024

Did you know that the LATE estimator was independently described in 1994 by Imbens & Angrist in Econometrica and Baker & Lindeman in Statistics in Medicine? onlinelibrary.wiley.com/doi/10.1002/... A delightful historical overview of LATE is now available www.tandfonline.com/doi/full/10....

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