Causal Analysis in Theory and Practice

July 19, 2012

A note posted by Elias Bareinboim

In the past week, I have been engaged in a discussion with Andrew Gelman and his blog readers┬áregarding causal inference, selection bias, confounding, and generalizability. I was trying to understand how his method which he calls “hierarchical modelling” would handle these issues and what guarantees it provides. Unfortunately, I could not reach an understanding of Gelman’s method (probably because no examples were provided).

Still, I think that this discussion having touched core issues of scientific methodology would be of interest to readers of this blog, the link follows:
http://andrewgelman.com/2012/07/long-discussion-about-causal-inference-and-the-use-of-hierarchical-models-to-bridge-between-different-inferential-settings/

Previous discussions took place regarding Rubin and Pearl’s dispute, here are some interesting links:
http://andrewgelman.com/2009/07/disputes_about/
http://andrewgelman.com/2009/07/more_on_pearlru/
http://andrewgelman.com/2009/07/pearls_and_gelm/
http://andrewgelman.com/2012/01/judea-pearl-on-why-he-is-only-a-half-bayesian/

If anyone understands how “hierarchical modeling” can solve a simple toy problem (e.g., M-bias, control of confounding, mediation, generalizability), please share with us.

Cheers,
Bareinboim

1 Comment »

  1. […] inferential settings, Elias Bareinboim (a computer scientist who is working with Judea Pearl) writes: In the past week, I have been engaged in a discussion with Andrew Gelman and his blog readers […]

    Pingback by Examples of the use of hierarchical modeling to generalize to new settings « Statistical Modeling, Causal Inference, and Social Science — July 23, 2012 @ 6:56 am

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