Dear friends in causality,<\/p>\n
This greeting from UCLA Causality blog contains:
\nA. News items concerning causality research,
\nB. New postings, publications, slides and videos,
\nC. New questions and some answers.<\/p>\n
1. Journal of Causal Inference – Vol. 1, Issue 2<\/strong> As always, submissions are welcome on all aspects of causal analysis, especially those deemed heretical.<\/p>\n 2. Causality book – new printing<\/strong> If you have an older printing and do not wish to buy another copy, all changes are marked in red here: 3. Special Issue on Counterfactuals<\/strong> 4. A Strange article in Science Magazine.<\/strong> 5. Calls for papers on Causality<\/strong> 5.2 The ACM TIST journal is planning a Special Issue on Causal Discovery and Inference, and has issued a call for papers. 6. Dennis Lindley, dead at 90<\/strong> 7. New postings on this blog.<\/strong> 8. New slides and videos available<\/strong> * Video of an introductory lecture presented to economists (at Stanford) is available here: 9. New scientific questions and some answers<\/strong> 420 – J. Pearl, “Reflections on Heckman and Pinto’s ‘Causal Analysis after Haavelmo”, 419 – Bareinboin, Lee, Honavar, Pearl “Transportability from Multiple Enironments with Limited Experiments” 417 – Pearl and Mohan “Recoverability and Testability of Missing Data.” 416 – J. Pearl “The Mathematics of Causal Inference” 414 – J. Pearl, “Understanding Simpson’s Paradox” 410 – Mohan, Pearl and Tian “Graphical Models for Inference with Missing Data” (Newly Revised) 363 – Pearl and Paz, “Confounding Equivalence in Causal Analysis” (Revised Oct 2013) Wishing you a happy and productive new year, Dear friends in causality, This greeting from UCLA Causality blog contains: A. News items concerning causality research, B. New postings, publications, slides and videos, C. New questions and some answers. 1. Journal of Causal Inference – Vol. 1, Issue 2 The second issue of the Journal of Causal Inference is on its way, and an […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2,16],"tags":[],"class_list":["post-1082","post","type-post","status-publish","format-standard","hentry","category-announcement","category-general"],"_links":{"self":[{"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1082","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=1082"}],"version-history":[{"count":0,"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/posts\/1082\/revisions"}],"wp:attachment":[{"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=1082"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=1082"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/causality.cs.ucla.edu\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=1082"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nThe second issue of the Journal of Causal Inference is on its way, and an on-line posting date has been set for December 23 2013. The first issue, can be viewed here:
\nhttp:\/\/www.degruyter.com\/view\/j\/jci.2013.1.issue-1\/issue-files\/jci.2013.1.issue-1.xml<\/a>
\nor here:
\nhttp:\/\/www.degruyter.com\/view\/j\/jci<\/a><\/p>\n
\nThe 3rd printing of Causality (2009, 2nd ed.) is finally out (as of Sept. 1), corrected and improved. <\/p>\n
\nhttp:\/\/bayes.cs.ucla.edu\/BOOK-09\/causality2-errata-updated7_3_13.pdf<\/a><\/p>\n
\nThe latest issue of Cognitive Science is dedicated to counterfactual reasoning. Edited by Stephen Sloman, the Table of Content and on-line version are available here:
\nhttp:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/cogs.2013.37.issue-6\/issuetoc<\/a><\/p>\n
\nTwo articles in Science Magazine and Nature were brought to our attention:
\n http:\/\/www.sciencemag.org\/content\/338\/6106\/496.abstract<\/a>
\n http:\/\/www.nature.com\/nphys\/journal\/v8\/n12\/full\/nphys2497.html<\/a>
\nThe author claims that causal effects can be inferred from correlation, using an extended version of Granger Causality.
\nTo me this sounds like squaring the circle; perhaps one of our readers can illuminate us.<\/p>\n
\n5.1 Isabell Guyon sent us a call for papers for Special Topic of JMLR on Causality and Experimental Design. See:
\nhttp:\/\/clopinet.com\/isabelle\/Projects\/NIPS2013\/Causality_Special_Topic_2014.html<\/a><\/p>\n
\nSee: http:\/\/tist.acm.org\/CFPs\/TIST-SI-CDI.html<\/a><\/p>\n
\nOn a sad note, Dennis Lindley, a pioneer in Bayesian inference died last week, at age 90.
\nLindley brought the “SEEING vs. DOING” distinction to the attention of the statistics community:
\nhttp:\/\/bayes.cs.ucla.edu\/BOOK-2K\/lindley-rev.pdf<\/a>
\nHe also adapted the causal interpretation of Simpson’s paradox ahead of his peers.
\nWe will miss his intellect, curiosity and integrity.
\nA true gentleman.<\/p>\n
\nSince our last greetings, the following items were posted on this blog (you can view them below).
\nAug. 9 , 2013, Larry Wasserman on JSM 2013<\/a>
\nOct. 26, 2013, Comments on Kenny’s Summary of Causal Mediation<\/a>
\nNov. 10, 2013, On Heckman and Pinto<\/a>
\nNov. 19, 2013, The Key to Understanding Mediation<\/a>
\nDec. 14 2013, “But where does the graph come from?”<\/a><\/p>\n
\n* Slides of the tutorial on “Causes and Counterfactuals” preseted at NIPS-2013 (by Pearl and Bareinboim) are available here:
\nhttp:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/nips-dec2013-pearl-bareinboim-tutorial.pdf<\/a>
\nhttp:\/\/www.cs.ucla.edu\/~eb\/nips-dec2013-pearl-bareinboim-tutorial-full.pdf<\/a><\/p>\n
\nhttp:\/\/gsb-mediasite.stanford.edu\/mediasite\/Play\/4ee5b390c7ef456c9ba0b11d1a519d4b1d<\/a><\/p>\n
\nThere are new postings on my home page
\n http:\/\/bayes.cs.ucla.edu\/csl_papers.html<\/a>
\nwhich might earn your attention. Among them:<\/p>\n
\n where I defend Haavelmo’s original theory of intervention against a Fisherian surrogate proposed in Heckman and Pinto (2013).
\n http:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/r420.pdf<\/a><\/p>\n
\n where we ask (and answer) whether it is possible to combine experimental findings from many heterogeneous studies to get what we need.
\n http:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/r419.pdf<\/a><\/p>\n
\n where we explain missing-data problems to the uninitiated using graphical models, and illustrate the concepts of recoverability and testability.
\n http:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/r417.pdf<\/a><\/p>\n
\n A summary of a Lecture given at JSM-2013, which compiles the main mathematical results in causal inference.
\n http:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/r416.pdf<\/a><\/p>\n
\n where I introduce a guessing game that exhibits perpetual reversals and argue that the paradox can safely be titled: “resolved”
\n http:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/r414.pdf<\/a><\/p>\n
\n where we take a fresh look at missing data problems from a causal inference perspective and propose a new taxonomy for misssing data mechanisms.
\n http:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/r410.pdf<\/a><\/p>\n
\nWe ask: When would an adjustment for T introduce the same bias as an adjustment for Z, and we answer it by extending the results of the 2010 version of this paper.
\nhttp:\/\/ftp.cs.ucla.edu\/pub\/stat_ser\/r343w.pdf<\/a><\/p>\n
\nJudea Pearl<\/p>\n","protected":false},"excerpt":{"rendered":"