Visual Logic of Instrumental Variables: Causal Inference Bootcamp

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  • Опубліковано 2 гру 2024

КОМЕНТАРІ • 13

  • @bettyaugust5623
    @bettyaugust5623 2 роки тому +2

    A lecturer that talks in a human way without unnecessary termology and actually explains concepts in a concise manner - THANK YOU FOR THIS SERIES!

  • @snoringinseattle
    @snoringinseattle 3 роки тому

    I am a UNC graduate student and I've been trying to grasp this concept from many different sources. This is the clearest of them all. I'm finally confident that I understand what iv is. Thank you professor!

  • @thonghuynh7962
    @thonghuynh7962 3 роки тому

    The best lecturer I ever had

  • @lizou761
    @lizou761 2 роки тому

    Very nice video! Another great book on this topic is "Mastering Metrics.“ Thanks

  • @oliviat978
    @oliviat978 4 роки тому +1

    Awesome examples. Thanks so much!

  • @joelrick1629
    @joelrick1629 3 роки тому

    Awesome work !

  • @LaminManjang-xx6dk
    @LaminManjang-xx6dk Місяць тому

    how many subjects have do and how many subject are compousery to do

  • @camilafloressanhueza7966
    @camilafloressanhueza7966 6 років тому +1

    Extremely helpful!!! Thank u very much

  • @arunaugustine568
    @arunaugustine568 8 років тому +2

    Super helpful video!!!

  • @googledude5649
    @googledude5649 5 років тому

    So the errorterm in this case is the pre-treatment variables ?

  • @LosMengers
    @LosMengers 8 років тому

    ¿Qué canción usan al inicio de sus videos?

  • @xavsaboss
    @xavsaboss Рік тому

    nice trim

  • @diegomabrary4974
    @diegomabrary4974 6 років тому +3

    I think there are two points that I am not agree with. One: randomize Instrument variable only remove the arrow from the confounders to Instrument, does not remove the backward dir. Two: Instrument variable does have some causal effect on the outcome, but not directly impact on the outcome. @author