Causal Analysis in Theory and Practice

Andrew Gelman and his blog readers followed-up with the previous discussion (link here) on his methods to address issues about causal inference and transportability of causal effects based on his “hierarchical modeling” framework, and I just posted my answer.

This is the general link for the discussion:
http://andrewgelman.com/2012/07/examples-of-the-use-of-hierarchical-modeling-to-generalize-to-new-settings/

Here is my answer:
http://andrewgelman.com/2012/07/examples-of-the-use-of-hierarchical-modeling-to-generalize-to-new-settings/#comment-92499

Cheers,
Bareinboim

In the past week, I have been engaged in a discussion with Andrew Gelman and his blog readers regarding 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

Dear friends in causality research,

This communication highlights a few meetings in the summer of 2012, that should be of interest to causality researchers. Naturally, these are biased in favor of those that were brought to my attention. If you know of more such meetings, feel free to post.

1.
July 22-26, 2012, Toronto, Canada
Annual Conference of the Association for Advancement of
Artificial Intelligence, AAAI-12,
http://www.aaai.org/Conferences/AAAI/2012/

I will present a lecture on “The Mechanization of Causal Inference, a Mini Turing-Test and Beyond”`
http://www.aaai.org/Conferences/AAAI/2012/aaai12turing.php
and Elias Bareinboim will present a completeness result for the transportability problem.
http://ftp.cs.ucla.edu/pub/stat_ser/r390.pdf

2.
Joint Statistical Meeting
JSM 2012, San Diego, CA, July 28-Aug 3, 2012
There are 73 papers and meetings on causal inference listed in the program, here they are: http://www.amstat.org/meetings/jsm/2012/onlineprogram/KeywordSearchResults.cfm

These include a day-long course on Targeted Learning: Causal Inference for Observational and Experimental Data
CE_08C Sun, 7/29/2012, 8:30 AM – 5:00 PM HQ-Indigo E
by Maya Petersen, Sherri Rose, Mark van der Laan, http://www.amstat.org/meetings/jsm/2012/onlineprogram/AbstractDetails.cfm?abstractid=304318

And J. Pearl tutorial “Causal Inference in Statistics: A gentle introduction” Sunday, July 17 4-6pm http://www.amstat.org/meetings/jsm/2012/onlineprogram/AbstractDetails.cfm?abstractid=304318

—————An Interesting Observation ——
In 2002, JSM-2002 had only 13 papers on causal inference, By any gauge, 73 is a positive sign of progress in the field.
—————end of interesting observation ——

3.
UAI2012, Catalina, CA, August 15-17, 2012
(Uncertainty in Artificial Intelligence)

Workshop on Causal Structure Learning, Aug. 18
http://www.stat.washington.edu/tsr/uai-causal-structure-learning-workshop/

Alison Gopnik will speak on “Babies, Brain and Bayes (Banquet Speech), Thursday, Aug. 16.,
and I will speak on “Do-Calculus Revisited” Aug. 17, 1:30 pm
http://www.auai.org/uai2012/invited.shtml

4.
Workshop on Networks Processes and Causality
Sept 3-6, 2012, Menorca, Spain
http://people.tuebingen.mpg.de/networks-workshop/

5.
MLSP 2012 Special Session on Causal Discovery
IEEE Workshop on Machine Learning for Signal Processing (MLSP 2012)
September 23-26 2012, Santander, Spain
http://mlsp2012.conwiz.dk/index.php?id=3D62

6.
Symposium on Causal Inference, University of Michigan,
December 12, 2012. Contact: Professor Yu Xie.

Miscellaneous
7.
Larry Wasserman has a new blog, and dedicated a page to befriending “causality”.
http://normaldeviate.wordpress.com/2012/06/18/48/

8.
A new book “Causality: Statistical Perspectives and Applications”,
C. Berzuini, P. Dawid and L. Bernardinelli (Eds.)
has just been published by Wiley (Chihester) July 2012: see
http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470665564.html .

Perpetual online access to the book is available on:
http://onlinelibrary.wiley.com/doi/10.1002/9781119945710.fmatter/summary

9.
Another new book appeared this month
R.H. Hoyle (Ed.) Handbook of Structural Equation Modeling, New York: Guilford Press.
It contains my chapter on “The Causal Foundations of SEM”
ttp://ftp.cs.ucla.edu/pub/stat_ser/r370.pdf

10.
Finally, the UCLA fruit basket offers a few fresh items, see http://bayes.cs.ucla.edu/csl_papers.html
One item of interest to economists-educators is:
Chen and Pearl “A Critical Examination of Econometrics Textbooks,” where we survey six influential econometric textbooks in terms of their mathematical treatment of causal concepts. The conclusions are revealing, if you click on http://ftp.cs.ucla.edu/pub/stat_ser/r395.pdf (And if you have ideas on reforming econometric education, please share.)

Wishing you an insightful and productive summer
Best,
Judea Pearl