Causal Analysis in Theory and Practice

September 15, 2016

Summer-end Greeting from the UCLA Causality Blog

Filed under: Uncategorized — bryantc @ 4:39 am

Dear friends in causality research,
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This greeting from UCLA Causality blog contains news and discussion on the following topics:

1. Reflections on 2016 JSM meeting.
2. The question of equivalent representations.
3. Simpson’s Paradox (Comments on four recent papers)
4. News concerning Causal Inference Primer
5. New books, blogs and other frills.

1. Reflections on JSM-2016
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For those who missed the JSM 2016 meeting, my tutorial slides can be viewed here: http://bayes.cs.ucla.edu/jsm-august2016.ppt

As you can see, I argue that current progress in causal inference should be viewed as a major paradigm shift in the history of statistics and, accordingly, nuances and disagreements are merely linguistic realignments within a unified framework. To support this view, I chose for discussion six specific achievements (called GEMS) that should make anyone connected with causal analysis proud, empowered, and mighty motivated.

The six gems are:
1. Policy Evaluation (Estimating “Treatment Effects”)
2. Attribution Analysis (Causes of Effects)
3. Mediation Analysis (Estimating Direct and Indirect Effects)
4. Generalizability (Establishing External Validity)
5. Coping with Selection Bias
6. Recovering from Missing Data

I hope you enjoy the slides and appreciate the gems.

2. The question of equivalent representations
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One challenging question that came up from the audience at JSM concerned the unification of the graphical and potential-outcome frameworks. “How can two logically equivalent representations be so different in actual use?”. I elaborate on this question in a separate post titled “Logically equivalent yet way too different.” http://causality.cs.ucla.edu/blog/index.php/2016/09/12/

3. Simpson’s Paradox: The riddle that would not die
(Comments on four recent papers)
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If you search Google for “Simpson’s paradox”, as I did yesterday, you would get 111,000 results, more than any other statistical paradox that I could name. What elevates this innocent reversal of associations to “paradoxical” status, and why it has captured the fascination of statisticians, mathematicians and philosophers for over a century are questions that we discussed at length on this (and other) blogs. The reason I am back to this topic is the publication of four recent papers that give us a panoramic view at how the understanding of causal reasoning has progressed in communities that do not usually participate in our discussions.  http://causality.cs.ucla.edu/blog/index.php/2016/08/24/

4. News concerning Causal Inference – A Primer
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We are grateful to Jim Grace for his in-depth review on Amazon: https://www.amazon.com/gp/customer-reviews/R2T3OB4WRGRRC0/ref=cm_cr_dp_d_rvw_ttl?ie=UTF8&ASIN=1119186846

For those of you awaiting the solutions to the study questions in the Primer, http://bayes.cs.ucla.edu/PRIMER/ I am informed that the Solution Manual is now available (to instructors) from Wiley. To obtain a copy, see page 2 of: http://bayes.cs.ucla.edu/PRIMER/CIS-Manual-PUBLIC.pdf However, rumor has it that a quicker way to get it is through your local Wiley representative, at https://professor.wiley.com/CGI-BIN/LANSAWEB?PROCFUN+PROF1+PRFFN15

If you encounter difficulties, please contact us at causality.ucla@gmail.com and we will try to help. Readers tell me that the solutions are more enlightening than the text. I am not surprised, there is nothing more invigorating than seeing a non-trivial problem solved from A to Z.

5. New books, blogs and other frills
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5.1
We are informed that a new book by Joseph Halpern, titled “Actual Causality”, is available now from MIT Press. (https://www.amazon.com/Actual-Causality-Press-Joseph-Halpern/dp/0262035022). Readers familiar with Halpern’s fundamental contributions to causal reasoning will not be surprised to find here a fresh and comprehensive solution to the age-old problem of actual causality. Not to be missed.

5.2
Adam Kelleher writes about an interesting math-club and causal-minded blog that he is orchestrating. See his post, http://causality.cs.ucla.edu/blog/index.php/2016/09/11/

5.3
Glenn Shafer just published a review paper: “A Mathematical Theory of Evidence turn 40” celebrating the 40th anniversary of the publication of his 1976 book “A Mathematical Theory of Evidence” http://www.glennshafer.com/assets/downloads/MathTheoryofEvidence-turns-40.pdf I have enjoyed reading this article for nostalgic reasons, reminding me of the stormy days in the 1980’s, when everyone was arguing for another calculus of evidential reasoning. My last contribution to that storm, just before sailing off to causality land, was this paper: http://ftp.cs.ucla.edu/pub/stat_ser/r136.pdf. Section 10 of Shafer’s article deals with his 1996 book “The Art of Causal Conjecture” My thought: Now, that the causal inference field has matured, perhaps it is time to take another look at the way Shafer views causation.

Wishing you a super productive Fall season.

J. Pearl

1 Comment »

  1. I just read your note in Edge. As I followed your story I was reminded many times of the work of Donald Davidson in philosophy of language.
    His interest was the formal and theoretical conditions of understanding.
    Not suprisingly his first great paper was on a casual theory of explanation.

    Comment by Conrad Johnson — October 26, 2016 @ 6:50 pm

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