Friends in causality research,
\nThis greeting from the UCLA Causality blog contains:<\/p>\n
A. An introduction to our newly published book,\u00a0Causal Inference in Statistics – A Primer,\u00a0Wiley 2016 (with M. Glymour and N. Jewell)
\nB. Comments on two other books: (1) R. Klein’s\u00a0Structural Equation Modeling and (2) L Pereira and\u00a0A. Saptawijaya’s on Machine Ethics.
\nC. News, Journals, awards and other frills.<\/p>\n
A. This book introduces core elements of causal inference into\u00a0undergraduate and lower-division graduate classes in statistics\u00a0and data-intensive sciences. The aim is to provide students with\u00a0the understanding of how data are generated and interpreted\u00a0at the earliest stage of their statistics education.\u00a0To that end, the book empowers students with models and\u00a0tools that answer nontrivial causal questions using\u00a0vivid examples and simple mathematics.\u00a0Topics include: causal models, model testing, effects of interventions,\u00a0mediation and counterfactuals, in both linear and\u00a0nonparametric systems.<\/p>\n The Table of Contents, Preface and excerpts from the four\u00a0chapters can be viewed here: B1 This book is unique in that it treats structural equation\u00a0models (SEMs) as carriers of causal assumptions and tools\u00a0for causal inference. Gone are the inhibitions and\u00a0trepidation that characterize most SEM texts in their treatments\u00a0of causation.<\/p>\n To the best of my knowledge, Chapter 8 in Kline’s\u00a0book is the first SEM text to introduce graphical criteria\u00a0for parameter identification — a long overdue tool B2 C. News, Journals, awards and other frills. The ASA Causality in Statistics Education Award is aimed at encouraging\u00a0the teaching of basic causal inference in introductory statistics\u00a0courses. Co-sponsored by Microsoft Research and Google, the prize\u00a0is motivated by the growing importance of introducing core\u00a0elements of causal inference into undergraduate and\u00a0lower-division graduate classes in statistics.\u00a0For more information, please see\u00a0http:\/\/www.amstat.org\/ Nominations and questions should be sent to the ASA office at\u00a0educinfo@amstat.org<\/a> . The nomination deadline is February 15, 2016<\/span><\/span>.<\/p>\n C.2.
\nOur publisher (Wiley) has informed us that the\u00a0book “Causal Inference in Statistics – A Primer”\u00a0by J. Pearl, M. Glymour and N. Jewell\u00a0is already available on Kindle, and will be available\u00a0in print Feb. 26, 2016<\/span><\/span>.
\nhttp:\/\/www.amazon.com\/
\nhttp:\/\/www.amazon.com\/Causal-
\nhttp:\/\/bayes.cs.ucla.edu\/
\nA book website providing answers to home-works\u00a0and interactive computer programs for simulation and analysis\u00a0(using dagitty)\u00a0 is currently under construction.<\/p>\n
\nWe are in receipt of the fourth edition of\u00a0Rex Kline’s book “Principles and Practice of Structural\u00a0Equation Modeling”,\u00a0http:\/\/psychology.concordia.
\nin a field that depends on identifiability for model\u00a0“fitting”.\u00a0Overall, the book elevates SEM education to new\u00a0heights and promises to usher a\u00a0renaissance for a field that, five decades ago, has pioneered\u00a0causal analysis in the behavioral sciences.<\/p>\n
\nMuch has been written lately on computer ethics,\u00a0morality, and free will. The new book “Programming Machine Ethics”\u00a0by Luis Moniz Pereira and Ari Saptawijaya\u00a0formalizes these concepts in the language of logic programming. See book announcement\u00a0http:\/\/www.springer.com\/gp\/
\nC1.
\nNominations are Invited for the Causality in Statistics Education Award\u00a0(Deadline is February 15, 2016<\/span><\/span>).<\/p>\n
\nIssue 4.1 of the Journal of Causal Inference is\u00a0scheduled to appear March 2016, with articles\u00a0covering all aspects of causal analysis. For\u00a0mission, policy, and submission information please\u00a0see: http:\/\/degruyter.com\/view\/j\/