Dear colleague in causality research,
This is an End-of-Winter Greetings from the UCLA Causality blog, welcoming you back to a spring-time discussion in causality-related issues.
This message contains
1. Topics under discussion
2. New results
3. Information on courses, lectures, and conferences.
1. Discussions inviting comments
1.1. “Principal Stratification – A goal or a tool?”
Posted for discussion by the International Journal of Biostatistics (IJB), this paper questions whether studies based on Principal Stratification target quantities that researchers truly care about.
If you have comments, ideas or objections, you are invited to communicate them to the IJB’s Editor, “Nicholas P. Jewell” <firstname.lastname@example.org> or/and, if you wish, cross-post them on this blog.
1.2. “Comments and Controversies: Graphical models, potential outcomes and causal inference: Comment on Lindquist and Sobel”
This note comments on a paper published in NeuroImage which argues (yes, again) that the potential outcome model is somehow superior, more rigorous or more principled than the structural models used in fMRI research. To further illuminate the logic of such claims I have added a section (4.4.2) in this paper:
which demonstrates how potential outcomes can be generated, on demand, from a simple structural model, and no one can tell where they came from. Enjoy.
1.3. “The Causal Mediation Formula – A practitioner guide to the assessment of causal pathways”
This paper present mediation analysis to researchers in the tradition of Baron and Keney (1986), and shows through examples how “the percentage explained by mediation” and “the percentage owed to mediation” are estimated in nonlinear models with both continuous and categorical variables.
1.4. Simpson’s Paradox
Sander Greenland brought to my attention a recent paper in Synthese (Sept. 28, 2010) claiming that Simpson’s paradox is NOT rooted in causal, but in some other kind of illusion. I remain convinced of the former, and have accordingly modified the Simpson Paradox entry in Wikipedia to reinforce the causal illusion theory. You might wish to add your take on the subject.
1.5. “The ETT Paradox (or, the curse of free will)”
This paradox would be appreciated by those who are fascinated, like me, by our ability to determine, from data alone, if one would have been better off acting differently than one actually did. This can lead to a cycle of inevitable regret, and provokes some naughty thoughts.
2. New Results
2.1. A newly posted paper, “Controlling Selection Bias in Causal Inference” http://ftp.cs.ucla.edu/pub/stat_ser/r381.pdf gives graphical and algebraic conditions for the removal of selection bias and the recovery of covariate-specific effect measures.
2.2. A new section (Section 5) in http://ftp.cs.ucla.edu/pub/stat_ser/r372.pdf generalizes the concept of transportability from experimental to observational studies,and shows how one can avoid re-learning things from scratch when moving to a new population, new domain, or a new environment.
2.3. After months of struggling with the literature of “surrogate endpoints” we feel that we now have a fairly satisfactory theory of surrogacy. It is based on the idea that a surrogate should serve not merely as a good predictor of outcomes, but also as ROBUST predictor of effects in the face of changing external conditions. See section 6 in http://ftp.cs.ucla.edu/pub/stat_ser/r372.pdf
3. Courses, Lectures and Conferences
3.1. Causal Inference Course
Thomas Richardson and Michael Hudgens are once again teaching Causal Inference June 13-15, 2011 in the Summer Institute here at U Washington. They have funds to support tuition waivers and some travel for students and postdocs. The website is http://depts.washington.edu/sismid/
3.2. 2011 Atlantic Causal Conference
The 2011 Atlantic Causal Conference will take place at the University of Michigan School of Public Health in Ann Arbor, Michigan, Thursday May 19th and Friday May 20th. See
Contact: Mike Elliott at email@example.com or Ben Hansen at firstname.lastname@example.org
3.3. Errata for Causality (2010)
FYI, Cambridge University Press has come up with a new printing of my book Causality, which corrects a few errors in the 2009 edition. Please advise students to insist on a copy saying “reprinted 2010”.
If you have an older copy, you can find the corrections marked in red here:
3.4. Lecture Slides available
Slides of my lecture on “What’s New in Causal Inference” can be viewed on my home page, second line from top.
You are welcome to use them in any way you choose. But usage for a good cause is recommended.
Looking forward to your postings, and may clarity prevail.