Rezultati pretraživanja
  1. 29. ruj 2018.

    Time-varying treatments: Part III of now online. Chapter 19 introduces key concepts, Chapter 20 explains treatment-confounder feedback, and Chapter 21 describes how g-methods deal with it. I wish this had been available when I started out in this business.

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  2. 5. ožu 2017.

    : Revised version available to download. New chapters coming soon.

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  3. 31. ožu 2019.

    Check out the updated code! Now with Stata by yours truly👇🏼👇🏼

  4. 2. lip 2018.
  5. 29. sij
  6. 20. stu 2019.

    Thank you and for making this important and comprehensive resource on available for free

  7. 14. stu 2019.

    Broke: writing casual when you meant to write causal Woke: writing causal when you meant to write casual

  8. 12. stu 2019.

    This is a great point. The is fantastic but should know where to dig deeper and why ...

  9. 20. lip 2019.

    Of all the things that excellent data scientists can do in their free time, I am so happy that Sam Finlayson () chose this. Thanks for helping us make the more accessible, Sam. I owe you one.

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  10. 2. sij 2019.

    Curious to know more? The gives a high-level introduction to causal inference & causal graphs. The is a more detailed, but still accessible, primer on all things causal inference (plus its free!). You can access it here:

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  11. 1. sij 2019.

    RT Our revised is now freely available. The book is organized in 3 parts of increasing difficulty: From counterfactuals & causal diagrams to treatment-confounder feedback & g-methods. Thanks to everyone who sent us…

  12. 17. pro 2018.

    Guess who is on chapter 7 of , 10 chapters to causal survival analysis. In case you have not started the book, it is like a book of magical spells for those in comparative effectiveness research.

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  13. 16. pro 2018.
    Odgovor korisnicima

    Enjoyed reading , & (my 5 yr old's favourite).Winnie's wand can change anything to anything with no side-effects. If we found one of these would all differences between & disappear in a puff of smoke?

  14. 30. stu 2018.

    Mind-blowing thread right here. Have been reading as much Seawall Wright as I can lately. 💡

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  15. 30. stu 2018.

    3/n Some of that "background knowledge" in real-world causal inference is that something can't be in the womb 70 years after it’s born. Absorb the tone of the rest of the preface, or read twitter feed, or the book. How do other readers see this?

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  16. 29. stu 2018.
    Odgovor korisniku/ci

    I recommend the —it’s accessible, comprehensive, and best of all free online.

  17. 27. stu 2018.

    Retweeting you to get something to read along with so I feel the discussion like in a classroom

  18. 22. stu 2018.

    Take home message from chapter 3 of "observational studies are conditionally randomized studies". I've never thought of them that way but defining them that way reinforce my trust in causal effect from obs studies. Yes smoking causes cancer!!!

  19. 15. stu 2018.

    Now in the NEJM results from a RCT get reported as thy were from an observational study - some editors need to read books on causality and what RCTs tell you

  20. 14. stu 2018.

    There is a reason there is standing room only at Javier Sanchez from talk on mediation analysis at . for some of the concepts

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