Covariate adjustment in randomized studies with time-to-event endpoints
Dr. Iván Díaz, Assistant Professor of Biostatistics at Weill Cornell Medicine, works on methods for statistical learning and causal inference from observational and randomized studies with complex designs and datasets. He discusses the advantages of covariate adjustment in randomized studies with time-to-event endpoints, and application of TMLE and Super Learning.

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Cross-validated Targeted Maximum Likelihood Estimation (CV-TMLE)

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Covariate adjustment in randomized clinical trials: from general theory to practical insights

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Targeted Learning: Towards a future informed by real world evidence

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2. An Introduction toTargeted Maximum Likelihood Estimation of Causal Effects

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This Chart Terrifies Electrical Engineers

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Avicii, Dua Lipa, Coldplay, Martin Garrix & Kygo, The Chainsmokers Style - SUMMER DEEP HOUSE Mix

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Penny Helps Sheldon Solve His Equation | The Big Bang Theory

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Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker

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How To Think SO Clearly People Assume You're Brilliant

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The French Do Not Care About Work

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AlphaFold - The Most Useful Thing AI Has Ever Done

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Microbiome expert: How to reset your gut overnight | Tim Spector

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But what is the Fourier Transform? A visual introduction.

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The Complete Web Development Roadmap

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The Riskiest Moment of the AI Bubble
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Everything we know about AI in 14 minutes – with Anthropic's Chloe Lubinski [ARC 2026]
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You’ll stop using ChatGPT after listening to this | Jonathan Pageau [ARC 2026]

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Backend web development - a complete overview

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This cell just changed biology

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