ALEXANDER Emeritus Professor of E-mail: [email protected] Web: http://www.statslab.cam.ac.uk/∼apd

EDUCATION 1967–69 University of London (Imperial College; University College) 1963–67 Cambridge University (Trinity Hall; Darwin College) 1956–63 City of London School QUALIFICATIONS 1982 ScD (Cantab.) 1970 MA (Cantab.) 1967 Diploma in Mathematical Statistics (Cantab.: Distinction) 1966 BA (Cantab.): Mathematics (Second Class Honours) 1963 A-levels: Mathematics and Advanced Mathematics (Double Distinction), Physics (Distinction) State Scholarship HONOURS AND AWARDS 2016 Fellow of the International Society for Bayesian Analysis 2015 Honorary Lifetime Member, International Society for Bayesian Analysis 2013 Network Scholar of The MacArthur Foundation Research Network on Law and Neuroscience 2002 DeGroot Prize for a Published Book in Statistical Science 2001 Royal Statistical Society: in Silver 1978 Royal Statistical Society: Guy Medal in Bronze 1977 G. W. Snedecor Award for Best Publication in Biometry EMPLOYMENT ETC. 2013– Emeritus Professor of Statistics, Cambridge University 2013– Emeritus Fellow, Darwin College Cambridge 2007–13 Professor of Statistics and Director of the Cambridge Statistics Initiative, Cambridge University 2011–13 Director of Studies in Mathematics, Darwin College Cambridge 2007–13 Professorial Fellow, Darwin College Cambridge 1989–2007 Pearson Professor of Statistics, University College London 1983–93 Head, Department of Statistical Science, University College London 1982–89 Professor of Probability and Statistics, University College London 1981–82 Reader in Probability and Statistics, University College London 1978–81 Professor of Statistics, Head of Statistics Section, and Director of the Statistical Laboratory, Department of Mathematics, The City University, London 1969–78 Lecturer in Statistics, University College London VISITING POSITIONS ETC. 2013–16 Visiting Fellow, Department of Mathematical Sciences, Durham University 2013–15 Visiting Fellow, Department of Criminology, Cambridge University 2010 Visiting Professor, University of Cagliari 2009–18 Honorary Professor, University of Hong Kong 2007–17 Honorary Professor, University College London 2001–02 Affiliate Professor, Gatsby Computational Neuroscience Unit, University College London 1982 Visiting Research Fellow, University of Wisconsin at Madison 1974–75 Visiting Lecturer in Statistics, University of British Columbia RESEARCH GRANTS

UK Research Councils 2009–12 Genetic variation, disease prediction and causation ∼£250,000 2007–12 Cambridge Statistics Initiative ∼£2.6M 2006–09 Geometrical methods for and decision ∼£250,000 2006–09 World of uncertainty (co-investigator) ∼£260,000 2006–09 Simplicity, complexity and modelling (co-investigator) ∼£250,000 1992–94 An abstract approach to expert systems ∼£100,000 1989–91 Bayesian analysis in expert systems ∼£30,000 1988–90 Probabilistic modelling for expert systems ∼£90,000 Visiting Fellowships 1985 M. J. Schervish ∼£6,000 1984 M. H. DeGroot ∼£2,000 1983–4 J. M. Dickey ∼£6,000

1 EEC

1989–93 Probabilistic reasoning on graphical structures ∼ECU20,000 with applications to expert systems

Home Office Forensic Science Service

1994–6 Research on DNA Statistics ∼£40,000

UK/Hong Kong Joint Research Scheme

1998–9 Conditional specification of multivariate ∼£5,000 probability distributions

European Science Foundation Scientific Programme on Highly Structured Stochastic Systems

2000 Short visit by Vanessa Didelez ∼FF 7,000 2000 Short visit by Dr Peter Gr¨unwald ∼FF10,000 2000 Research kitchen, Probabilistic expert systems ∼FF30,000 and genetics

Leverhulme Trust

2014–16 Emeritus Fellowship £18,920 2003–08 Evidence, inference and enquiry: Towards an ∼£970,000 integrated science of evidence 2001–04 Bayesian networks for forensic inference ∼£100,000 from genetic markers

Isaac Newton Trust

2012 in genomic ∼£ 14,000 2007–12 Cambridge Statistics Initiative: Building bridges ∼£125,000

PROFESSIONAL SOCIETIES

Royal Statistical Society

2015– Statistics and Law Section Committee 2013–15 Statistics and Law Working Group 1993 Chartered Statistician 1992 Joint Editor, Journal, Series B 1987–89 Chairman, Research Section 1981–82 Vice-President 1978–80 Honorary Secretary, Research Section 1975–78 Associate Editor, Journal, Series B

Read Papers 1990 Fisherian inference in likelihood and prequential frames of reference 1987 Symmetry models and hypotheses for structured data layouts 1978 in 1973 Marginalization paradoxes in Bayesian and structural inference (with M. Stone and J. V. Zidek) Institute of Mathematical Statistics

1979 Elected Fellow 1977–82 Associate Editor, Annals of Statistics

International Statistical Institute

1978 Elected Member

Biometrika Trust

1992–96 Editor, 1984–92, 1996– Trustee

International Society for Bayesian Analysis

2005–9 Editor, Bayesian Analysis 2000 President 1998 Director

2 FURTHER PROFESSIONAL ACTIVITIES

2015– Technical Advisory Committee, Center for Statistics and Applications in Forensic Evidence, Iowa State University 2012– Group to Individual Committee, MacArthur Foundation Law and Neuroscience Network, USA 2012 ASA Committee on Establishment of an International Prize in Statistics 2011– Editorial Board, Journal of Causal Inference 2010 External Assessor, APRC Review of the Department of Statistics, London School of Economics 2009 Institute for Mathematical Sciences Advisory Board, Imperial College 2008–12 Board of Managers, Kuwait Foundation Fund 2007 President’s Advisory Board, Carnegie Mellon University Machine Learning Department 2006–8 Academy of Medical Sciences Working Party on Non-Experimental Methods 1989 External Assessor, Appointment Committee for Chair of Statistics, University of Durham 1988–91 UK Medicines Commission 1987– Trustee, Neuroendocrinology Charitable Trust 1987–89 Chairman, Board of Studies in Statistics, University of London 1983–91 Editorial Board, Oxford University Press Statistical Science Series 1982–85 SERC Statistics Panel 1978–91 Royal College of Physicians Computer Committee

External Examining

1998–2001 University of Kent 1995–97 Chief External Examiner for Combined Sciences, Hong Kong Baptist University 1992–94 University of Ulster 1986–90 Imperial College of Science, Technology and Medicine 1986–89 University College of Swansea 1982–85 University of Hong Kong 1980–83 University of Surrey

Conference Organisation

2013 Organiser, Special Topic Session on Probability Forecasting, 59th World Statistics Conference, Hong Kong 2011 Joint Organiser, Darwin College Lecture Series on “Beauty”, Cambridge 2010 Joint Organiser, Third Workshop on Game-Theoretic Probability and Related Topics, Royal Holloway University of London 2009 Joint Organiser, Machine Learning Summer School, Cambridge 2009–10 Co-Convenor, Mellon Sawyer Seminar on Modelling Futures: Understanding Risk and Uncertainty, Cambridge 2009 Joint Organiser, Molpage Training Programme on Causal Inference: State of the Art, Cambridge 2009 Joint Organiser, Communicating Complex Statistical Evidence, Cambridge 2008 Joint Organiser, LMS Symposium on Mathematical Aspects of Graphical Models, Durham 2008 Organiser, Cambridge Statistics Initiative 1-Day Meeting, Cambridge 2007 Programme Committee Chair, British Academy Conference on Enquiry, Evidence and Facts: An Interdisciplinary Conference 2005 Programme Committee, 10th International Workshop on Artificial Intelligence and Statistics, Barbados 2004 Scientific Programme Committee, 3rd Winter Workshop on Statistics and Computer Science, Ein-Gedi, Israel 2001 Organizer, DNA Workshop Meeting, Lewes 2001 Programme Committee, 8th International Workshop on Artificial Intelligence and Statistics, Key West, Florida 2000 Joint Organiser and Head of UK Delegation, International Conference on Foundations of Statistical Inference, Jerusalem 2000 Joint Conference President, 6th World Meeting of the International Society for Bayesian Analysis, Crete 2000 Joint Organiser, HSSS Research Kitchen on Probabilistic Expert Systems for Genetic Analysis, San Vigilio, Italy 1999 Scientific Programme Committee and Seminar Organiser, Research Programme on Causal Interpretation and Identification of Conditional Independence Structures, Fields Institute, Toronto 1998 Joint Organiser, HSSS Workshop on Structural Learning in Graphical Models, Tirano, Italy 1991, 1994, 1998, Organising Committee, Valencia International Meetings on 2002, 2006, 2010 1986 Joint Academic Organiser, RSS/SERC Research Workshop on Asymptotic Statistical Inference, Edinburgh 1982, 1986 Joint Technical Convenor: Institute of Statisticians Conferences on Practical Bayesian Statistics, Cambridge

In addition, I have served on numerous University and Professional committees.

INVITED PRESENTATIONS, ETC.

2016 Programme on Probability and Statistics in Forensic Science, Isaac Newton Institute, Cam- bridge 2016 Paper Highlights from Bayesian Analysis Session, Joint Statisticsl Meetings, Chicago 2016 Paper Highlights from Statistics and Public Policy Session, Joint Statisticsl Meetings, Chicago

3 2016 International Society for Bayesian Analysis, Sardinia 2016 Keynote Speaker, Soci´et´eFran¸caisede Statistique, Montpellier 2015 Center for Statistics and Applications in Forensic Evidence Kickoff Event, Ames, Iowa 2015 RSS Statistics and the Law Section Meeting on Epidemiological Evidence and Tort Litigation, London 2015 International Workshop on Causality, Counterfactuals, and Legal Responsibility, Sassari 2015 Fifth Conference of the European Philosophy of Science Association, D¨usseldorf 2015 Lindley Memorial Session, Joint Statistical Meetings, Seattle 2015 Greek Stochastics, Crete 2015 Danish Society of Theoretical Statistics, Copenhagen 2015 Keynote Speaker, UK Causal Inference Meeting, Bristol 2015 Fifth Workshop on Game-Theoretic Probability and Related Topics, Guanajuato, Mexico 2014 Keynote Speaker, 9th International Conference on Forensic Inference and Statistics, Leiden 2014 47th Scientific Meeting of the Italian Statistical Society, Cagliari 2014 Keynote Speaker, Korean Statistical Society Spring Meeting, Daejeon 2014 KNAW Colloquium on Dependence Logic, Amsterdam 2013 12th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Utrecht 2013 High-Dimensional Inference with Applications, Kent 2013 RSS Bayes 250 Meeting, London 2013 Methodological Issues in the Special Sciences, Bertinoro, Italy 2013 Recent Advances in Statistical Inference, Padua 2013 Seminar on Dependence Logic: Theory and Applications, Dagstuhl, Germany 2013 Max Planck Intelligent Systems Colloquium, T¨ubingen,Germany 2012 Probabilistic Expert Systems for Forensic Genetics, Rome 2012 Symposium on Conditional and Direct Causal Effects, Jena 2012 Lecture course, Universit`aRoma Tre 2012 The Hidden Side of DNA Profiles, Rome 2012 Causal Inference and Dynamic Decisions in Longitudinal Studies, Bristol 2011 30th Fisher Memorial Lecture, Cambridge 2011 8th International Conference on Forensic Inference and Statistics, Seattle 2011 Guest Lecturer, Vienna International Summer University 2011 Hierarchical Models and Markov Chain Monte Carlo, Crete 2011 Causal Inference in the Health Sciences, Bologna 2011 Workshop on Geometric and Algebraic Statistics 3, Warwick 2010 Information Geometry and its Applications III, Leipzig 2010 Third Workshop on Game-Theoretic Probability and Related Topics, Royal Holloway University of London 2010 Young Researchers in Mathematics 2010, Cambridge 2010 Saw Swee Hock Lecture in Statistics, University of Hong Kong 2009 Perspectives on Causation, School of Law, University of Aberdeen 2009 Atlantic Causal Modeling Conference, University of Pennsylvania 2009 Causal Inference: State-of-the-Art, Cambridge 2009 Mixing and Epidemiology, 2009 Communicating Complex Statistical Evidence, Cambridge 2008 Causality: Objectives and Assessment. Neural Information Processing Systems Workshop, Whistler 2008 Tutorial, Neural Information Processing Systems Conference, Vancouver 2008 Gruppo Ematologi Forensi Italiani, Padova 2008 LMS Symposium on Mathematical Aspects of Graphical Models, Durham 2008 The Rˆoleand Evaluation of Evidence in Economic Analysis, Bologna 2008 Franklin Institute Awards Symposium, Philadelphia 2008 Geometric Aspects of Conditional Independence and Information, Leipzig 2007 British Academy Conference on Enquiry, Evidence and Facts: An Interdisciplinary Conference 2007 Reassessing the Paradigms of Building, Oberwolfach, Germany 2007 Academy of Experts, London 2007 Evidence in the Human Sciences, Bologna 2007 Confirmation, Induction and Science, London School of Economics 2007 Seymour Geisser Memorial Lecture, University of Minnesota 2007 Graphic and Visual Representations of Evidence and Inference in Legal Settings, Cardozo Law School, New York 2006 de Finetti Centenary Meeting, Bologna 2006 Pluralism and Causality in the Sciences, London School of Economics 2006 Medical Thinking: What Do We Know? CRUK, London 2006 40th Anniversary Celebrations, Department of Statistics, Glasgow 2006 Causality and Probability in the Sciences, University of Kent 2006 Teaching Evidence and Fact Analysis, Institute of Advanced Legal Studies, London 2006 Causation, Probability and Decision, Sydney University 2006 Bayesian Reasoning Workshop, Monash University 2006 Distinguished Lecture in Computer Science, Queen Mary, University of London 2005 Second International Conference on Information Geometry, Tokyo 2005 21st Congress of the International Society for Forensic Genetics, Azores 2005 Second Workshop on Combining Probability and Logic, London School of Economics 2005 British Society for Philosophy of Science Annual Conference, Manchester

4 2005 International Conference on Statistics, Hong Kong 2005 Human Identification E-Symposium 2005 2005 Sixth International Conference on Forensic Statistics, Tempe, Arizona 2004 Royal Statistical Society Conference, Manchester 2004 International Summer School on ‘Causality, Uncertainty and Ignorance’, Konstanz, Germany 2004 PASCAL Workshop on Learning-Theoretic and Bayesian Inductive Principles, London 2004 Information Processing and Management of Uncertainty, Perugia 2004 19th Annual Darwin College Lecture Series, Cambridge 2003 GSS Assistant Statistician & Statistical Officer Annual Conference, Reading 2003 Workshop on Paradigms of Model Building, Dortmund 2003 MIR@C Workshop on Bayesian Networks and Micro-Array Analysis, Warwick 2003 CISHE Colloquium on Transitions, University College London 2003 54th Session of the International Statistical Institute, Berlin (Invited Paper Meeting Organiser) 2003 Workshop on Complexity and Inference, Rutgers University 2003 Workshop on Statistical Learning in Classification and , Eindhoven 2002 Fifth International Conference on Forensic Statistics, Venice 2002 AMS Summer Research Conference on Emerging Issues in Longitudinal Data Analysis, Mount Holyoke College, Massachusetts 2002 Conference on Causality: Metaphysics and Methods, London School of Economics 2001 Workshop on Recent Developments and Applications in the Statistical Analysis of Discrete Structures, Munich 2001 Conference on Statistical Models and Computationally Intensive Methods for Estimation and Prediction, Bressanone, Italy 2001 Conference on Causality and Statistics, Snowbird, Utah 2001 Rietz Lecturer, IMS Annual Meeting, Atlanta, Georgia 2001 Seminar on Inference Principles and Model Selection, Dagstuhl, Germany 2001 ISBA Regional Meeting, Laguna Beach 2001 Symposium on Bayes’s Theorem, The British Academy, London 2001 HSSS Workshop on Structural Stochastic Systems for Individual Behaviours, Louvain-la- Neuve, Belgium (Discussant) 2001 Eighth International Workshop on Artificial Intelligence and Statistics, Key West, Florida 2000 International Conference on Foundations of Statistical Inference, Jerusalem 2000 Seminar in Honour of Abner Shimony, Bologna 2000 DINA Research Kitchen on Probabilistic Expert Systems for Genetic Analysis, Skagen, Den- mark 2000 HSSS Final Workshop, Luminy, France 2000 21st Meeting of the International Society for Clinical , Trento, Italy (Discussant) 2000 AMS Summer Research Conference on Bayes, Frequentist and Likelihood Inference: A Syn- thesis, Mount Holyoke College, Massachusetts 2000 Fourth Conference on Logic and the Foundations of the Theory of Games and Decisions, Turin 2000 Sixth World Meeting of the International Society for Bayesian Analysis, Crete 2000 International Conference on Philosophical Aspects of Bayesianism, King’s College London 2000 Workshop on Forecast Validation and Risk Assessment, Humboldt University, Berlin 2000 HSSS Research Kitchen on Probabilistic Expert Systems for Genetic Analysis, San Vigilio, Italy 1999 Fourth International Conference on Forensic Statistics, North Carolina State University 1999 Research Seminars on ‘Conditional Independence Structures and Graphical Models’ and ‘Causal Interpretation of Graphical Models’, Research Programme on Causal Interpretation and Identification of Conditional Independence Structures, Fields Institute, Toronto 1999 Second European Conference on Highly Structured Stochastic Systems, Pavia 1999 52nd Session of the International Statistical Institute, Helsinki (Invited Paper Meeting Or- ganiser) 1999 Workshop on On-Line Decision Making, Rutgers University 1999 International Workshop on Objective Bayesian Methodology, Valencia 1999 Uncertainty 99 (Seventh International Workshop on Artificial Intelligence and Statistics), Fort Lauderdale, Florida 1998 HSSS Workshop on Structural Learning in Graphical Models, Tirano, Italy 1998 Special Invited Speaker, Joint UAI/ICML/COLT Meetings, Madison, Wisconsin 1998 Conference on Automated Learning and Discovery, Pittsburgh 1998 Sixth Valencia International Meeting on Bayesian Statistics 1997 Programme on Neural Networks and Machine Learning, Isaac Newton Institute, Cambridge 1997 AMS-IMS-SIAM Summer Research Conference on Graphical Markov Models, Influence Dia- grams, and Bayesian Belief Networks, Seattle 1997 Joint Statistical Meetings (ASA), Anaheim (Session organiser) 1997 International Society for Bayesian Analysis, Istanbul 1997 International Symposium on Contemporary Multivariate Analysis and its Applications, Hong Kong (Session organiser and speaker) 1997 Tutorial, Sixth International Workshop on Artificial Intelligence and Statistics, Fort Laud- erdale, Florida 1996 NATO Advanced Study Institute on Learning in Graphical Models, Erice, Sicily 1996 Fourth World Congress of the Bernoulli Society, Vienna 1996 Third International Conference on Forensic Statistics, Edinburgh 1995 Third Brazilian Bayesian Statistics Meeting, Ouro Preto 1995 Closing Address, Sixth Latin American Congress on Probability and Statistics, Vi˜nadel Mar, Chile

5 1995 Algebraic and Combinatorial Methods in Multivariate Analysis, Oberwolfach, Germany 1995 Research Seminar on Probability and Causality, Aalborg, Denmark 1995 Second International Workshop on Bayesian Robustness, Rimini, Italy 1995 Mahalanobis Memorial Lectures, Indian Statistical Institute: Delhi, Bangalore, Calcutta 1994 Second European Science Foundation Workshop on Highly Structured Stochastic Systems, Wiesbaden, Germany 1994 First European Science Foundation Workshop on Highly Structured Stochastic Systems, Cortona, Italy 1994 Drug Information Association 5th European Workshop on Statistical Methodology in Clinical Research, Edinburgh 1993 International Workshop on Hierarchical Modelling, Rio de Janeiro 1993 Computer Vision Programme, Isaac Newton Institute, Cambridge 1993 Second DeGroot Memorial Lecture, Carnegie-Mellon University 1993 49th Session of the International Statistical Institute, Florence 1993 First Multinational Riverboat Conference on Bayesian Econometrics and Statistics, Basel–Amsterdam 1992 International Symposium on Social Gerontology, Jaen, Spain 1992 Royal Statistical Society Conference, Sheffield 1992 Institute of Statisticians Conference on Practical Bayesian Statistics, Nottingham 1992 Fifth Purdue International Symposium on Statistical Decision Theory and Related Topics 1992 International Symposium on Multivariate Analysis and its Applications, Hong Kong 1991 Conference on Recent Developments of Exchangeable Random Processes and their Statistical Applications, Cortona, Italy 1991 Fourth Valencia International Meeting on Bayesian Statistics 1990 Lecture course, University of Perugia, Italy 1990 Royal Statistical Society Fisher Centenary Meeting, London 1989 18th National Statistics Meeting, Santiago de Compostela, Spain 1989 RSS/SERC Research Workshop on Expert Systems and Statistics, Edinburgh 1989 Lecture Course, Bocconi University, Milan 1988 Joint Statistical Meetings, New Orleans 1988 14th George Zyskind Memorial Lecture, Iowa State University 1987 Third Valencia International Meeting on Bayesian Statistics 1986 Second Catalan International Symposium on Statistics, Barcelona 1986 Institute of Statisticians Conference on Practical Bayesian Statistics, Cambridge 1986 RSS/SERC Research Workshop on Asymptotic Statistical Inference, Edinburgh 1985 Lecture course, Department of Biostatistics, University of Valencia 1984 20th Gregynog Statistical Conference 1984 Royal Statistical Society 150th Anniversary Conference, London 1984 Israel Statistical Association Conference on Foundations of Statistical Inference, Tel Aviv 1983 British Society for the Philosophy of Science Annual Conference, Brighton 1983 Special Invited Paper, Institute of Mathematical Statistics Meeting, Nashville 1982 European Meeting of Statisticians, Palermo 1982 Royal Statistical Society Conference, York 1982 Lecture Course, University of London Postgraduate Statistics Series 1981 Conference on Exchangeability in Probability and Statistics, Rome 1980 Conference on , Rome 1979 International Meeting on Bayesian Statistics, Valencia 1978 Dutch Statistical Meeting, Lunteren 1978 Institute of Mathematical Statistics Conference, San Diego 1977 Lecture course, Department of Statistics, Carnegie-Mellon University 1977 Lecture Course, Istituto per le Applicazione del Calcolo, Rome 1976 European Meeting of Statisticians, Grenoble 1976 First European Conference on the Foundations and Applications of Bayesian Methods, Fontainebleau 1974 Research Conference, Department of Theoretical Statistics, Aarhus University

Additionally I have given numerous invited research seminars at Universities in the UK and abroad, and have proposed or seconded the vote of thanks on nine Royal Statistical Society read papers.

TEACHING

Postgraduate Courses

Advanced Statistics and Inference Advanced Statistics Practical Statistics Comparative Statistical Methods Probabilistic Expert Systems and Applied Bayesian Methods Image Analysis Communication Workshop Monte Carlo Inference

Undergraduate Courses

Elementary Statistics Stochastic Processes Statistical Prediction Analysis Probability Frequency Data Multivariate Analysis

6 and Inference Decision Analysis Linear Methods and Analysis of Computational Techniques for Statistics Stochastic Systems Statistical Inference Stochastic Methods in Finance Principles of Statistics

Ancillary Courses

Probability for Mathematicians Statistics for Medical Students Statistics for Systems and Management Evidence and Proof (Ll.M. Students) Graduate School Foundation Course

External Courses

Industrial Statistics Lucas Institute for Engineering Production Bayesian Statistics for Science, Engineer- George Washington University ing, Medicine and Management Statistical Methods in Reliability George Washington University RSS/EPSRC Graduate Training Programme; Fundamentals of Statistical Causality Dipartimento di Economia, Universit`aRoma Tre Causality Machine Learning Summer School, Cambridge

MAJOR CONSULTING ACTIVITIES

Auto-Roulette Performance Analysis of Electronic Gaming Machines Department of Health/British Dental Association Measurement of Dentists’ Workload (Report deposited in House of Commons Library) W. S. Atkins Management Consultants/Anglian Water/South-West Water Verification of Statistical Methodology and Software for Water Company Asset Management Plans Glaxo Group Research Limited/Fastmalt Limited An Expert System for Assessing Adverse Drug Reactions Various Solicitors Adviser/expert witness on the interpretation of statistical evidence — especially DNA profile evidence Railtrack PLC Expert Knowledge Elicitation

RESEARCH INTERESTS

My research has been largely motivated by the desire to understand and explore the connexions between logical and philosophical principles of inference, mathematical structures, and data-analysis. Much of my work is a critical examination of the logical Foundations of Statistics, both from a general standpoint and in respect of particular schools of thought — especially Bayesian, but also Likelihood, Structural and Fiducial. Early work on the Marginalization Paradox in improper continues to stimulate debate. I have a particular interest in Bayesian Decision Theory, and have developed and applied general decision- theoretic ideas to clarify the theory of Optimal Experimental Design. Other Bayesian research interests include: Coherent Combination of Expert Opinions; Matrix Distribution Theory and Bayesian Multivariate Analysis (where work with BiQi Fang has drawn attention to undesirable properties of conjugate prior distributions in problems with many variables, and suggested some better-behaved alternatives); Model Uncertainty; and Maximum Entropy and Robust Bayes Analysis (which, in work with Peter Gr¨unwald, have been shown to be two sides of the same coin). Over 30 years ago I made contributions to a novel approach to statistical inference from the viewpoint of abstract Differential Geometry, which have proved significant in the later detailed development of that topic by Amari and others. I have once more become engaged in this area, and am extending it to statistical decision theory. With Steffen Lauritzen and Matthew Parry I have developed a complete characterisation of local proper scoring rules, which encourage honesty when assessing probability distributions, while depending only on the assessment made in the neighborhood of the realised outcome. I introduced and developed the general axiomatic theory of, and associated notation for, Conditional Inde- pendence. As well as being a valuable tool for formulating and solving a great variety of conceptual and technical problems, this supplies a unifying thread drawing together many seemingly unrelated concepts of sta- tistical inference. More recently I developed a novel abstract mathematical framework, the Separoid, which supports the application of these ideas to a wide of other ‘irrelevance’ concepts, of independent interest. This work has been widely applied and extended by workers in Artificial Intelligence. A major research effort over many years was devoted to Probabilistic Expert Systems, now more popularly known as Bayesian Networks: a multi-faceted topic which applies graph-theoretic representations to analyse, structure and manipulate complex multivariate distributions. My theory of Conditional Independence played a crucial rˆolein this. The book Probabilistic Networks and Expert Systems, written with Robert Cowell, Steffen Lauritzen & and published by Springer in 1999, was awarded the first DeGroot Prize for a Published Book in Statistical Science. An important philosophical attitude underpinning almost all my work is a ‘positivist’ emphasis on observables, and on the falsifiability of inferences. In particular this has guided my approach to the interpretation, assessment and validation of probability statements. I introduced the Criterion of validity for probability forecasts, and developed this into a novel philosophical theory of Objective Probability. The same attitude provided the impetus for my introduction of Prequential Analysis, a general approach to problems of statis- tical inference and data analysis which takes seriously the problem of making and criticising statistical forecasts.

7 Theoretically, it allows for very broad extension of classical ideas such as estimation efficiency, or consistent model selection, and has many pleasing properties. Practically, it provides a more generally applicable and in- terpretable alternative to cross-validation. Prequential Analysis has been successfully applied to the monitoring and improvement of the predictive performance of Bayesian Networks. It has close and interesting links with Bayesian Inference, with the theory of Stochastic Complexity, with Algorithmic Complexity Theory, and with Computational Learning Theory (COLT). With Vladimir Vovk I developed a new general mathematical theory of Prequential Probability, based on game-theoretic rather than measure-theoretic foundations. Another long-term research theme was Symmetry Modelling, which, extending de Finetti’s ideas of exchange- ability, uses symmetry judgements and group representation theory to guide the construction, interpretation and analysis of statistical models. It has some purely technical connexions with the randomization theory of exper- imental design. A complete algebraic theory was developed for the general ‘poset block structure’. Even for familiar simple balanced experimental layouts the symmetry viewpoint has provided new insights and methods of data analysis, and it also leads to new forms, analyses and understandings of the ‘’ of the . Because of competing priorities much of this work remained unpublished, but, stimulated by an invitation to deliver a ‘Fisher Memorial Lecture’, I am reviving my attention to it. I have been developing new formulations and techniques for the conduct of Causal Inference, a topic of great current interest; this has links with both Symmetry Modelling and Bayesian Networks. My general world view being antipathetic to currently popular explications of statistical causality based on counterfactual variables, I have been investigating the extent to which sensible causal inferences can be justified without recourse to counterfactuals. In particular, I have shown that a natural decision-theoretic approach, using influence diagrams, can clarify and simplify many problems of causal inference, including , direct and indirect causal effects, and effects of dynamic interventions. This work has been presented widely to philosophical as well as statistical audiences and outlets, and is currently being applied to address important practical problems such as medical decision-making and policy analysis. I have been interested in the application of Probability and Statistics to a variety of subject areas, in particular to Medicine (especially medical diagnosis and decision-making), Crystallography, Reliability (especially Software Reliability) and, currently, Legal Reasoning. I have acted as expert advisor or witness in a number of legal cases, including notably that of Sally Clark who was accused of murdering her two baby sons, and others involving DNA profiling and fibre transfer. This has led me to a thorough theoretical examination of the use of Probability and Statistics for Forensic Identification, as well as to some study of genetic population structure. I led an international research group that developed probabilistic expert systems to analyse complex criminal and paternity DNA cases. This has also produced new methodology for estimating DNA mutation rates. I have an interest in a range of logical and intellectual issues relating to the general concept of Evidence.I developed and directed a large-scale interdisciplinary programme involving 11 Departments across 7 Faculties at University College London, which led to publication of the book ‘Evidence, Inference and Enquiry’.

November 3, 2016

8 A. P. DAWID Publications

[1] Dawid, A. P. (1970). On the limiting normality of posterior distributions. Proc. Cam. Phil. Soc. 67, 625–633. [2] Stone, M. and Dawid, A. P. (1972). Expectation consistency of inverse probability distributions. Biometrika 59, 486–489. [3] Dawid, A. P. and Stone, M. (1972). Un-Bayesian implications of improper Bayes inference in routine statistical problems. Biometrika 59, 369–375. [4] Dawid, A. P. and Stone, M. (1973). Expectation consistency and generalized Bayes inference. Ann. Statist. 1, 478–485. DOI:10.1214/aos/1176342413 [5] Dawid, A. P. (1973). Posterior expectations for large observations. Biometrika 60, 664–667. [6] Dawid, A. P., Stone, M. and Zidek, J. V. (1973). Marginalization paradoxes in Bayesian and struc- tural inference (with Discussion). J. Roy. Statist. Soc.B 35, 189–233. [7] Dawid, A. P. (1975). Invited discussion of ‘Defining the curvature of a statistical problem (with applications to second-order efficiency)’, by B. Efron. Ann. Statist. 3, 1231–1234. [8] Dawid, A. P. (1975). On the concepts of sufficiency and ancillarity in the presence of nuisance parameters. J. Roy. Statist. Soc.B 37, 248–258. [9] Dawid, A. P. (1976). Properties of diagnostic data distributions. Biometrics 32, 647–658. [10] Dawid, A. P. (1976). Invited discussion of ‘Plausibility inference’, by O. E. Barndorff-Nielsen. J. Roy. Statist. Soc.B 39, 123–125. [11] Dawid, A. P. (1977). Conformity of inference patterns. Recent Developments in Statistics, edited by J. R. Barra, B. van Cutsen, F. Brodeau and G. Romier. North-Holland Press, 245–256. [12] Dawid, A. P. (1977). Invariant distributions and analysis of variance models. Biometrika 64, 291– 297. [13] Dawid, A. P. (1977). Spherical matrix distributions and a multivariate model. J. Roy. Statist. Soc. B 39, 254–261. [14] Dawid, A. P. (1977). Further comments on some comments on a paper by . Ann. Statist. 5, 1249. DOI:10.1214/aos/1176344011 [15] Dawid, A. P. and Dickey, J. M. (1977). Likelihood and Bayesian inference from selectively reported data. J. Amer. Statist. Assoc. 72, 845–850. [16] Brooks, R. J., Dawid, A. P., Galbraith, J. I., Galbraith, R. F., Smith, A. F. M. and Stone, M. (1978). A note on forecasting car ownership. J. Roy. Statist. Soc.A 141, 64–68. [17] Dawid, A. P. (1978). Extendibility of spherical matrix distributions. J. Multivariate Anal. 8, 559– 566. [18] Dawid, A. P. and Skene, A. M. (1979). Maximum likelihood estimation of observer error rates using the EM algorithm. J. Roy. Statist. Soc.C (Applied Statistics) 28, 20–28. [19] Dawid, A. P. (1979). Conditional independence in statistical theory (with Discussion). J. Roy. Statist. Soc.B 41, 1–31. [20] Dawid, A. P. (1979). Some misleading arguments involving conditional independence. J. Roy. Statist. Soc.B 41, 249–252. [21] Dawid, A. P., Stone, M. and Zidek, J. V. (1980). Comments on Jaynes’ paper ‘Marginalization and prior probabilities’. Bayesian Analysis in Econometrics and Statistics: Essays in Honor of Harold Jeffreys, edited by A. Zellner. North-Holland Publishing Company, 79–82. [22] Dawid, A. P. (1980). Conditional independence for statistical operations. Ann. Statist. 8, 598–617. DOI:10.1214/aos/1176345011

1 [23] Dawid, A. P. (1980). A Bayesian look at nuisance parameters (with Discussion). Bayesian Statistics, edited by J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith. University of Valencia Press, 167–184. [24] Dawid, A. P. (1980). Invited discussion of ‘ and Bayes’ inference in scientific modelling and robustness’, by G. E. P. Box. J. Roy. Statist. Soc.A 143, 406–408. [25] Dawid, A. P. (1981). Some matrix-variate distribution theory: notational considerations and a Bayesian application. Biometrika 68, 265–274. [26] Dawid, A. P. and Guttman, I. (1981). Conjugate Bayesian inference for structural models. Comm. Stat.—Theory Methods A 10, 739–748. [27] Dawid, A. P. (1982). Intersubjective statistical models. Exchangeability in Probability and Statistics, edited by G. Koch and F. Spizzichino. North-Holland Publishing Company, 217–232. [28] Dawid, A. P. (1982). The well-calibrated Bayesian (with Discussion). J. Amer. Statist. Ass. 77, 605–613. Reprinted in: Probability Concepts, Dialogue and Beliefs, edited by O. F. Hamouda and J. C. R. Rowley. Edward Elgar Publishing Ltd. (1997), 165–173. [29] Dawid, A. P. and Stone, M. (1982). The functional-model basis of fiducial inference (with Discussion). Ann. Statist. 10, 1054–1074. DOI:10.1214/aos/1176345970 [30] Dawid, A. P. (1982). Invited discussion of ‘The statistical analysis of compositional data’, by J. Aitchison. J. Roy. Statist. Soc.B 44, 162–163. [31] Dawid, A. P. (1983). Inference, Statistical: I. Encyclopedia of Statistical Sciences vol. 4, edited by S. Kotz, N. L. Johnson and C. B. Read. Wiley-Interscience, 89–105. [32] Dawid, A. P. (1983). Invariant Prior Distributions. Encyclopedia of Statistical Sciences vol. 4, edited by S. Kotz, N. L. Johnson and C. B. Read. Wiley-Interscience, 228–236. [33] Dawid, A. P. and Smith, A. F. M., Eds. (1983). Practical Bayesian Statistics. Longman. [34] Dawid, A. P. (1984). Causal inference from messy data. (Invited discussion of ‘The nature and discovery of structure’, by J. W. Pratt and R. Schlaifer). J. Amer. Statist. Ass. 79, 22–24. Reprinted in: The Methodology of Econometrics vol. I, edited by D. J. Poirier. Edward Elgar Publishing Ltd. (1994), 368–370. [35] Dawid, A. P. (1984). Present position and potential developments: some personal views. Statistical theory. The prequential approach (with Discussion). J. Roy. Statist. Soc.A 147, 278–292. [36] Dawid, A. P. (1984). Invited discussion of ‘Extreme point models in Statistics’, by S. L. Lauritzen. Scand. J. Statist. 11, 85. [37] Dawid, A. P. (1985). Probability, symmetry and frequency. Brit. J. Phil. Sci. 36, 107–128. [38] Consonni, G. and Dawid, A. P. (1985). Invariant normal Bayesian linear models and experimen- tal designs. Bayesian Statistics 2 , edited by J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith. Elsevier Science Publishers B. V., 629–644. [39] Dawid, A. P. (1985). The impossibility of inductive inference. (Invited discussion of ‘Self-calibrating priors do not exist’, by D. Oakes.) J. Amer. Statist. Ass. 80, 340–341. [40] Consonni, G. and Dawid, A. P. (1985). Decomposition and Bayesian analysis of invariant normal linear models. Linear Algebra Appl. 70, 21–49. [41] Dawid, A. P. (1985). Invariance and independence in multivariate distribution theory. J. Multivariate Anal. 17, 304–315. [42] Dawid, A. P. (1985). Calibration-based empirical probability (with Discussion). Ann. Statist. 13, 1251–1285. DOI:10.1214/aos/1176349736 Reprinted in: Probability Concepts, Dialogue and Beliefs, edited by O. F. Hamouda and J. C. R. Rowley. Edward Elgar Publishing Ltd. (1997), 174–208. [43] Dickey, J. M., Dawid, A. P. and Kadane, J. B. (1986). Subjective-probability assessment methods for multivariate-t and matrix-t models. Bayesian Inference and Decision Techniques, edited by P. K. Goel and A. Zellner, Chapter 12. Elsevier Science Publishers B. V., 177–195. [44] Dawid, A. P. (1986). A Bayesian view of statistical modelling. Bayesian Inference and Decision Techniques, edited by P. K. Goel and A. Zellner, Chapter 25. Elsevier Science Publishers B. V., 391–404.

2 [45] Dawid, A. P. (1986). Probability Forecasting. Encyclopedia of Statistical Sciences vol. 7, edited by S. Kotz, N. L. Johnson and C. B. Read. Wiley-Interscience, 210–218. [46] Dawid, A. P. (1986). Invited discussion of ‘On the consistency of Bayes estimates’, by P. Diaconis and D. Freedman. Ann. Statist. 14, 40–41. DOI:10.1214/aos/1176349834 [47] Dawid, A. P. (1986). Invited discussion of ‘On principles and arguments to likelihood’, by M. Evans, D. A. S. Fraser and G. Monette. Can. J. Statist. 14, 196–197. [48] Dawid, A. P. and Smith, A. F. M., Eds. (1987). Practical Bayesian Statistics. (Special issue of The Statistician, vol. 36, nos. 2–3.) [49] Dawid, A. P. (1987). The difficulty about conjunction. The Statistician 36, 91–97. [50] Dawid, A. P. (1987). Invited discussion of ‘Savage revisited’, by G. Shafer. Statistical Science 1, 488–492. DOI:10.1214/ss/1177013520 [51] Dawid, A. P. (1987). Invited discussion of ‘Estimation and inference by compact coding’, by C. S. Wallace and P. R. Freeman, and ‘Stochastic complexity’, by J. Rissanen. J. Roy. Statist. Soc.B 49, 253–254. [52] Dawid, A. P. (1988). Symmetry models and hypotheses for structured data layouts (with Discussion). J. Roy. Statist. Soc.B 50, 1–34. [53] Dawid, A. P. (1988). The infinite regress and its conjugate analysis (with Discussion). Bayesian Statistics 3 , edited by J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith. Oxford University Press, 95–110. [54] Dawid, A. P. and Gillies, D. A. (1989). A Bayesian analysis of Hume’s argument concerning miracles. Philosophical Quarterly 39, 57–65. [55] Lauritzen, S. L., Dawid, A. P., Larsen, B. N. and Leimer, H. G. (1990). Independence properties of directed Markov fields. Networks 20, 491–505. [56] Dawid, A. P. (1991). Fisherian inference in likelihood and prequential frames of reference (with Discussion). J. Roy. Statist. Soc.B 53, 79–109. [57] Royal Statistical Society Working Party (1991). Statistics and statisticians in drug regulation in the . J. Roy. Statist. Soc.A 154, 413–419. [58] Hutchinson, T. A., Dawid, A. P., Spiegelhalter, D. J., Cowell, R. G. and Roden, S. (1991). Computer aids for probabilistic assessment of drug safety. I. A spreadsheet program. Drug Information Journal 25, 29–39. [59] Hutchinson, T. A., Dawid, A. P., Spiegelhalter, D. J., Cowell, R. G. and Roden, S. (1991). Computer aids for probabilistic assessment of drug safety. II. An expert system. Drug Information Journal 25, 41–48. [60] Dawid, A. P. (1991). Probability and proof: some basic concepts. Appendix to Analysis of Evidence, by T. J. Anderson and W. L. Twining. Weidenfeld and Nicolson, 389–435. [61] Cowell, R. G., Dawid, A. P., Hutchinson, T. A. and Spiegelhalter, D. J. (1991). A Bayesian expert system for the analysis of an adverse drug reaction. Artificial Intelligence in Medicine 3, 257–270. [62] Spiegelhalter, D. J., Dawid, A. P., Hutchinson, T. A. and Cowell, R. G. (1991). Probabilistic expert systems and graphical modelling: a case study in drug safety. Phil. Trans. R. Soc. Lond. 337, 387–405. [63] Dawid, A. P. (1992). Applications of a general propagation algorithm for probabilistic expert sys- tems. Statistics and Computing 2, 25–36. [64] Cowell, R. G. and Dawid, A. P. (1992). Fast retraction of evidence in a probabilistic expert system. Statistics and Computing 2, 37–40. [65] Dawid, A. P. (1992) Prequential data analysis. In Current Issues in Statistical Inference: Essays in Honor of D. Basu, edited by M. Ghosh and P. K. Pathak. IMS Lecture Notes–Monograph Series 17, 113–126. DOI:10.1214/lnms/1215458842 [66] Bernardo, J. M., Berger, J. O., Dawid, A. P. and Smith, A. F. M., Eds. (1992). Bayesian Statistics 4 . Oxford University Press.

3 [67] Dawid, A. P. (1992). Prequential analysis, stochastic complexity and Bayesian inference (with Discussion). Bayesian Statistics 4 , edited by J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith. Oxford University Press, 109–125. [68] Dawid, A. P. and Fang, B. Q. (1992). Conjugate Bayes discrimination with infinitely many variables. J. Mult. Anal. 41, 27–42. [69] Seillier-Moiseiwitsch, F., Sweeting, T. J. and Dawid, A. P. (1992). Prequential tests of model fit. Scand. J. Statist. 19, 45–60. [70] Dawid, A. P. (1993). Invited discussion of ‘The logic of probability’, by V. G. Vovk. J. Roy. Statist. Soc.B 55, 341–343. [71] Seillier-Moiseiwitsch, F. and Dawid, A. P. (1993). On testing the validity of sequential probability forecasts. J. Amer. Statist. Ass. 88, 355–359. [72] Cowell, R. G., Dawid, A. P. and Spiegelhalter, D. J. (1993). Sequential model criticism in proba- bilistic expert systems. IEEE Trans. Pattern Recognition and Machine Intelligence 15, 209–219. [73] Fang, B. Q. and Dawid, A. P. (1993). Asymptotic properties of conjugate Bayes discrete discrimi- nation. J. Mult. Anal. 46, 83–96. [74] Spiegelhalter, D. J., Dawid, A. P., Lauritzen, S. L. and Cowell, R. G. (1993). Bayesian analysis in expert systems (with Discussion). Statistical Science 8, 219–283. DOI:10.1214/ss/1177010888 [75] Dawid, A. P. (1993). Taking prediction seriously. Bull. I. S. I. 55, Book 3, 3–13. [76] Dawid, A. P. and Wang, J. (1993). Fiducial prediction and semi-Bayesian inference. Ann. Statist. 21, 1119–1138. DOI:10.1214/aos/1176349253 [77] Dawid, A. P. and Lauritzen, S. L. (1993). Hyper Markov laws in the statistical analysis of decom- posable graphical models. Ann. Statist. 21, 1272–1317. DOI:10.1214/aos/1176349260 (Correction: Ann. Statist. 23 (1995), 1864. DOI:aos/1176324328) [78] Cowell, R. G., Dawid, A. P., Hutchinson, T. A., Roden, S. and Spiegelhalter, D. J. (1993). Bayesian networks for the analysis of drug safety. The Statistician 42, 369–384. [79] Dawid, A. P. (1994). Foundations of probability. Companion Encyclopedia of the History and Phi- losophy of the Mathematical Sciences, edited by I. Grattan-Guinness. Routledge, Vol. 2, 1399–1406. [80] Dawid, A. P. (1994). The island problem: coherent use of identification evidence. Chapter 11 of Aspects of Uncertainty: A Tribute to D. V. Lindley, edited by P. R. Freeman and A. F. M. Smith. J. Wiley and Sons, 159–170. [81] Dawid, A. P. (1994). Selection paradoxes of Bayesian inference. In Multivariate Analysis and its Applications, edited by T. W. Anderson, K. T. Fang and I. Olkin. IMS Lecture Notes-Monograph Series 24, 211–220. DOI:10.1214/lnms/1215463797 [82] Dawid, A. P., Kjaerulff, U. and Lauritzen, S. L. (1995). Hybrid propagation in junction trees. In Advances in Intelligent Computing — IPMU 94 , edited by B. Bouchon-Meunier, R. R. Yager and L. A. Zadeh. Springer-Verlag Lecture Notes in Computer Science 945, 87–97. [83] Dawid, A. P., DeGroot, M. H. and Mortera, J. (1995). Coherent combination of experts’ opinions (with Discussion). TEST 4, 263–313. [84] Dawid, A. P. (1995). Invited discussion of ‘Causal diagrams for empirical research’, by J. Pearl. Biometrika 82, 689–690. [85] Dawid, A. P. and Mortera, J. (1996). Coherent analysis of forensic identification evidence. J. Roy. Statist. Soc.B 58, 425–443. [86] Bernardo, J. M., Berger, J. O., Dawid, A. P. and Smith, A. F. M., Eds. (1996). Bayesian Statistics 5 . Oxford University Press. [87] Cowell, R. G., Dawid, A. P. and Sebastiani, P. (1996). A comparison of sequential learning methods for incomplete data. Bayesian Statistics 5 , edited by J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith. Oxford University Press, 533–541.

4 [88] Fang, B. Q. and Dawid, A. P. (1996). Comparison of full Bayes and Bayes-least squares criteria for normal discrimination. Chinese J. Applied Prob. and Stat. 12, 401–410. [89] Dawid, A. P. (1996). Invited discussion of ‘Markov random field priors for univariate density es- timation’, by R. L. Wolpert and M. Lavine. In Bayesian Robustness, edited by J. O. Berger, B. Betr`o,E. Moreno, L. R. Pericchi, F. Ruggeri, G. Salinetti, and L. Wasserman. IMS Lecture Notes–Monograph Series 29, 267–268. [90] Dawid, A. P. and Evett, I. W. (1997). Using a graphical method to assist the evaluation of compli- cated patterns of evidence. J. Forensic Sci. 42, 226–231. [91] Dawid, A. P. (1997). Prequential analysis. Encyclopedia of Statistical Sciences, Update Volume 1, edited by S. Kotz, C. B. Read and D. L. Banks. Wiley-Interscience, 464–470. [92] Dawid, A. P. (1997). Invited discussion of ‘Non-informative priors do not exist. A dialogue with Jos´eM. Bernardo’. J. Statist. Plan. Inf . 65, 178–180. [93] Dawid, A. P. (1998). Conditional independence. Encyclopedia of Statistical Sciences, Update Volume 2, edited by S. Kotz, C. B. Read and D. L. Banks. Wiley-Interscience, 146–155. [94] Dawid, A. P. (1998). Modelling issues in forensic inference. In 1997 ASA Proceedings, Section on Bayesian Statistics, 182–186. [95] Skouras, K. and Dawid, A. P. (1998). On efficient point prediction systems. J. Roy. Statist. Soc.B 60, 765–780. [96] Dawid, A. P. and Mortera, J. (1998). Forensic identification with imperfect evidence. Biometrika 85, 835–849. (Correction: Biometrika 86 (1999), 974.) [97] Dawid, A. P. and Evett, I. W. (1998). Authors’ response to ‘Commentary on Dawid, A. P. and Evett, I. W. Using a graphical method to assist the evaluation of complicated patterns of evidence. J. Forensic Sci. (1997) Mar; 42(2): 226–231.’ by Ira J. Rimson. J. Forensic Sci. 43, 251. [98] Dawid, A. P. and Studen´y,M. (1999). Conditional products: An alternative approach to conditional independence. In Artificial Intelligence and Statistics 99 , edited by D. Heckerman and J. Whittaker. Morgan Kaufmann, 32–40. [99] Dawid, A. P. and Vovk, V. G. (1999). Prequential probability: Principles and properties. Bernoulli 5, 125–162. http://projecteuclid.org/euclid.bj/1173707098 [100] Bernardo, J. M., Berger, J. O., Dawid, A. P. and Smith, A. F. M., Eds. (1999). Bayesian Statistics 6 . Oxford University Press. [101] Dawid, A. P. and Pueschel, J. (1999). Hierarchical models for DNA profiling using heteroge- neous databases (with Discussion). Bayesian Statistics 6 , edited by J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith. Oxford University Press, 187–212. [102] Cowell, R. G., Dawid, A. P., Lauritzen, S. L. and Spiegelhalter, D. J. (1999). Probabilistic Networks and Expert Systems. Springer, xii + 321 pp. [103] Dawid, A. P. and Sebastiani, P. (1999). Coherent dispersion criteria for optimal experimental design. Ann. Statist. 27, 65–81. DOI:10.1214/aos/1018031101 [104] Dawid, A. P. (1999). Who needs counterfactuals? Chapter 3 of Causal Models and Intelligent Data Management, edited by A. Gammerman. Springer–Verlag, 33–50. [105] Dawid, A. P., van Boxel, D. W., Mortera, J. and Pascali, V. L. (1999). Inference about disputed paternity from an incomplete pedigree using a probabilistic expert system. Bull. Int. Statist. Inst. 58, Contributed Papers Book 1, 241–242. [106] Dawid, A. P. (1999). Discussion of the papers by Rissanen and by Wallace and Dowe. (Invited dis- cussion of ‘Hypothesis Selection and Testing by the MDL Principle’, by J. Rissanen, and ‘Minimum Message Length and Kolmogorov Complexity’, by C. S. Wallace and D. L. Dowe.) The Computer Journal 42, 323–326. [107] Skouras, K. and Dawid, A. P. (1999). On efficient probability forecasting systems. Biometrika 86, 765–784. [108] Dawid, A. P. (2000). Causal inference without counterfactuals (with Discussion). J. Amer. Statist. Ass. 95, 407–448. Reprinted without discussion in: D. Corfield and J. Williamson (Eds.), Founda- tions of Bayesianism, Kluwer Applied Logic Series (2001), 37–74.

5 [109] Dawid, A. P. (2000). Invited discussion of ‘The Philosophy of Statistics’, by D. V. Lindley. J. Roy. Statist. Soc.D 49, 325–326. [110] Dawid, A. P. (2001). Some variations on variation independence. In Artificial Intelligence and Statis- tics 2001 , edited by T. Jaakkola and T. Richardson. Morgan Kaufmann, 187–191. [111] Dawid, A. P. (2001). Comment on Stockmarr’s ‘Likelihood ratios for evaluating DNA evidence when the suspect is found through a database search’ (with response by A. Stockmarr). Biometrics 57, 976–980. [112] Dawid, A. P. (2001). Separoids: A mathematical framework for conditional independence and irrel- evance. Ann. Math. Artificial Intelligence 32, 335–372. [113] Dawid, A. P. and Lauritzen, S. L. (2001). Compatible prior distributions. In Bayesian Methods with Applications to Science, Policy and Official Statistics, edited by Edward George. Monographs of Official Statistics, Eurostat, 109–118. [114] Dawid, A. P., Mortera, J. and Pascali, V. L. (2001). Non-fatherhood or mutation? A probabilistic approach to parental exclusion in paternity testing. Forensic Science International 124, 55–61. [115] Fang, B. Q. and Dawid, A. P. (2002). Nonconjugate Bayesian regression on many variables. J. Statist. Plan. Inf. 103, 245–261. [116] Dawid, A. P. (2002). Counterfactuals: Help or hindrance? (Invited discussion of ‘Estimating Causal Effects’, by G. Maldonado and S. Greenland.) Int. J. Epidemiology 31, 429–430. [117] Dawid, A. P. (2002). Bayes’s theorem and weighing evidence by juries. In Bayes’s Theorem, edited by Richard Swinburne. Proc. Brit. Acad. 113, 71–90. [118] Dawid, A. P. (2002). Influence diagrams for causal modelling and inference. Intern. Statist. Rev. 70, 161–189. Corrigenda, ibid., 437. [119] Dawid, A. P. (2002). Invited discussion of ‘Chain graph models and their causal interpretations’, by S. L. Lauritzen and T. S. Richardson. J. Roy. Statist. Soc.B 64, 348–51. [120] Gr¨unwald, P. D. and Dawid, A. P. (2002). Game theory, maximum generalized entropy, minimum discrepancy, robust Bayes and Pythagoras. In ITW 2002 – Proceedings of the 2002 IEEE Information Theory Workshop. ISBN 0-7803-7629-3. IEEE, Bangalore, India, 94–97. [121] Dawid, A. P., Mortera, J., Pascali, V. L. and van Boxel, D. W. (2002). Probabilistic expert systems for forensic inference from genetic markers. Scand. J. Statist. 29, 577–595. http://tinyurl.com/2ft4ehm [122] Dawid, A. P. (2003). An object-oriented Bayesian network for estimating mutation rates. In Proceed- ings of the Ninth International Workshop on Artificial Intelligence and Statistics, January 3–6 2003, Key West, Florida, edited by Christopher M. Bishop and Brendan J. Frey. ISBN 0-9727358-0-1. http://tinyurl.com/39bmh. [123] Mortera, J., Dawid, A. P. and Lauritzen, S. L. (2003). Probabilistic expert systems for DNA mixture profiling. Theor. Pop. Biol. 63, 191–205. [124] Dawid, A. P. (2003). Causal inference using influence diagrams: The problem of partial compliance (with Discussion). In Highly Structured Stochastic Systems, edited by Peter J. Green, Nils L. Hjort and . Oxford University Press, 45–81. [125] Bernardo, J. M., Bayarri, J. M., Berger, J. O., Dawid, A. P., Heckerman, D., Smith, A. F. M. and West, M., Eds. (2003). Bayesian Statistics 7 . Oxford University Press. [126] Dawid, A. P., Mortera, J., Dobosz, M. and Pascali, V. L. (2003). Mutations and the probabilistic approach to incompatible paternity tests. In Progress in Forensic Genetics 9 (Proceedings from the 19th Congress of the International Society for Forensic Haemogenetics), International Congress Series, Vol. 1239, edited by B. Brinkmann and A. Carracedo. Elsevier Science, Amsterdam, 637–638. [127] Vicard, P. and Dawid, A. P. (2004). A statistical treatment of biases affecting the estimation of mutation rates. Mutation Research 547, 19–33. [128] Dawid, A. P. (2004). Which likelihood ratio? (Comment on ‘Why the effect of prior odds should accompany the likelihood ratio when reporting DNA evidence’, by Ronald Meester and Marjan Sjerps). Law, Probability & Risk 3, 65–71. [129] Gr¨unwald, P. D. and Dawid, A. P. (2004). Game theory, maximum entropy, minimum discrepancy, and robust Bayesian decision theory. Ann. Statist. 32, 1367–1433. DOI:10.1214/009053604000000553

6 [130] Dawid, A. P. (2004). Probability, causality and the empirical world: A Bayes–de Finetti–Popper– Borel synthesis. Statistical Science 19, 44–57. DOI:10.1214/088342304000000125 [131] Dawid, A. P. (2005). Statistics on trial. Significance 2, 6–8. [132] Dawid, A. P. (2005). Probability and statistics in the law. In Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, January 6–8 2005, Barbados, edited by Zoubin Ghahramani and Robert G. Cowell. http://tinyurl.com/br8fl [133] Dawid, A. P. (2005). Probability and proof. On-line Appendix to Analysis of Evidence (Second Edition), by T. J. Anderson, D. A. Schum and W. L. Twining, Cambridge University Press (2005), 88 pp. http://www.cambridge.org/download_file/203379 [134] Dawid, A. P. and Lauritzen, S. L. (2006). The geometry of decision theory. Proceedings of the Second International Symposium on Information Geometry and its Applications (12–16 December 2005), University of Tokyo, 22–28. [135] Dawid, A. P., Mortera, J. and Vicard, P. (2006). Representing and solving complex DNA iden- tification cases using Bayesian networks. In Progress in Forensic Genetics 11 (Proceedings of the 21st International ISFG Congress) (A. Amorim, F. Corte-Real and N. Morling, Eds.). International Congress Series, Vol. 1288. Elsevier Science, Amsterdam, 484–491. DOI:10.1016/j.ics.2005.09.115 [136] Vicard, P and Dawid, A. P. (2006). Remarks on: “Paternity analysis in special fatherless cases without direct testing of alleged father” [Forensic Science International 146S (2004) S159–S161]. Forensic Science International 163, 158–160. DOI:10.1016/j.forsciint.2005.11.016 [137] Didelez, V., Dawid, A. P. and Geneletti, S. (2006). Direct and indirect effects of sequential treat- ments. In Proc. 22nd Annual Conference on Uncertainty in Artificial Intelligence (R. Dechter and T. S. Richardson, Eds.). AUAI Press, Arlington, Virginia, 138–146. [138] Dawid, A. P. (2007). Counterfactuals, hypotheticals and potential responses: a philosophical exam- ination of statistical causality. In Causality and Probability in the Sciences, edited by F. Russo and J. Williamson. London: College Publications, Texts In Philosophy Series Vol. 5, 503–532. [139] Dawid, A. P. (2007). The geometry of proper scoring rules. Annals of the Institute of Statistical Mathematics 59, 77–93. http://www.ism.ac.jp/editsec/aism/pdf/059 1 0077.pdf ¯ ¯ [140] Dawid, A. P., Mortera, J. and Vicard, P. (2007). Object-oriented Bayesian networks for complex forensic DNA profiling problems. Forensic Science International 169, 195–205. DOI:10.1016/j.forsciint.2006.08.028 [141] Bernardo, J. M., Bayarri, J. M., Berger, J. O., Dawid, A. P., Heckerman, D., Smith, A. F. M. and West, M., Eds. (2007). Bayesian Statistics 8 . Oxford University Press. [142] Sir Michael Rutter, Philip Dawid, Aroon Hingorani, Richard Horton, Peter Jones, Kay-Tee Khaw, Bill Kirkup, Geoff Mulgan, Catherine Peckham, Andrew Pickles, Robert Souhami and Geoff Watts (2007). Identifying the Environmental Causes of Disease: How Should We Decide What to Believe and When to Take Action? Working Group Report, Academy of Medical Sciences, London, 144 pp. [143] Hepler, A. B., Dawid, A. P. and Leucari, V. (2007). Object-oriented graphical representations of complex patterns of evidence. Law, Probability & Risk 6, 275–293. DOI:10.1093/lpr/mgm005 [144] Vicard, P., Dawid, A. P., Mortera, J. and Lauritzen S. L. (2008). Estimating mutation rates from paternity casework. Forensic Science International: Genetics 2, 9–18. DOI:10.1016/j.fsigen.2007.07.002 [145] Mortera, J. and Dawid, A. P. (2008). Probability and evidence. In Handbook of Probability Theory with Applications, edited by T. Rudas. Sage Publications, 403–422. [146] Dawid, A. P. (2008). Statistics and the law. In Evidence, edited by Andrew Bell, John Swenson- Wright and Karin Tybjerg. Cambridge University Press, 119–148. DOI:10.2277/0521839610

7 [147] Dawid, A. P. and Didelez, V. (2008). Identifying optimal sequential decisions. In Proc. 24th Annual Conference on Uncertainty in Artificial Intelligence (D. McAllester and P. Myllymaki, Eds.). AUAI Press, 113–120. http://tinyurl.com/3899qpp [148] Dawid, A. P. (2008). Comments on “Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds”, by Tilmann Gneiting, Larissa I. Stanberry, Eric P. Grimit, Leonhard Held and Nicholas A. Johnson. Test 17, 243–244. DOI:10.1007/s11749-008-0118-6 [149] Dawid, A. P. and Galavotti, M. C. (2009). de Finetti’s subjectivism, objective probability, and the empirical validation of probability assessments. In Bruno de Finetti, Radical Probabilist (M. C. Galavotti, Ed.). London: College Publications, 97–114. [150] Dawid, A. P. (2010). Beware of the DAG! In Proceedings of the NIPS 2008 Workshop on Causality, edited by I. Guyon, D. Janzing and B. Sch¨olkopf. Journal of Machine Learning Research Workshop and Conference Proceedings 6, 59–86. http://tinyurl.com/33va7tm [151] Dawid, A. P. (2010). Seeing and doing: The Pearlian synthesis. In Heuristics, Probability and Causal- ity: A Tribute to Judea Pearl (R. Dechter, H. Geffner and J. Y. Halpern, Eds.). London: College Publications, 309–325. [152] Dawid, A. P., Mortera, J. and Vicard, P. (2010). Paternity testing allowing for uncertain mutation rates. In The Oxford Handbook of Applied Bayesian Analysis (A. O’Hagan and M. West, Eds.). Oxford University Press, 188–215. [153] Guo, H. and Dawid, A. P. (2010). Sufficient covariates and linear propensity analysis. In Proceedings of the Thirteenth International Workshop on Artificial Intelligence and Statistics (AISTATS) 2010, Chia Laguna, Sardinia, Italy, May 13-15, 2010 , edited by Y. W. Teh and D. M. Titterington. Journal of Machine Learning Research Workshop and Conference Proceedings 9, 281–288. http://tinyurl.com/33lmuj7 [154] Dawid, A. P. and Didelez, V. (2010). Identifying the consequences of dynamic treatment strategies: A decision-theoretic overview. Statistical Surveys 4, 184–231. DOI:10.1214/10-SS081 [155] Dawid, A. P., de Rooij, S., Shafer, G., Shen, A., Vereshchagin, N. and Vovk, V. (2011). Insuring against loss of evidence in game-theoretic probability. Statistics and Probability Letters 81, 157–162. DOI:10.1016/j.spl.2010.10.013 [156] Dawid, A. P. (2011). Basu on ancillarity. In Selected Works of Debabrata Basu (A. DasGupta, Ed.). New York: Springer, 5–8. http://tinyurl.com/6kf2zo3 [157] Aitken, C. G. G. and 35 others. (2011). Guest editorial. Expressing evaluative opinions: A position statement. Science and Justice 51, 1–2. DOI:10.1016/j.scijus.2011.01.002 [158] Geneletti, S. and Dawid, A. P. (2011). Defining and identifying the effect of treatment on the treated. In Causality in the Sciences (P. McKay Illari, F. Russo and J. Williamson, Eds.). Oxford University Press, 728–749. [159] Egeland, T., Dawid, A. P., Mortera, J., Mostad, P. and Tillmar, A. (2011). Response to: DNA identification by pedigree likelihood ratio accommodating population substructure and mutations. Investigative Genetics 2: 7. DOI:10.1186/2041-2223-2-7 [160] Dawid, A. P. (2011). Posterior model probabilities. In Philosophy of Statistics (P. S. Bandyopadhyay and M. Forster, Eds.). New York: Elsevier, 607–630. [161] Dawid, A. P. and Vicard, P. (2011). Still further remarks on: “Paternity analysis in special fatherless case without direct testing of alleged father” [Forensic Science International 146S (2004) S159–S161] and remarks on it [FSI 163 (2006) 158–160, FSI 172 (2007) e6–e8]. Forensic Science International 207, e63. DOI:10.1016/j.forsciint.2010.12.016 [162] Dawid, A. P. (2011). The role of scientific and statistical evidence in assessing causality. In Perspec- tives on Causation (R. Goldberg, Ed.). Oxford: Hart Publishing, 133–147.

8 [163] Dawid, A. P., Twining, W. L. and Vasilaki, D., Eds. (2011). Evidence, Inference and Enquiry (Pro- ceedings of the British Academy, vol. 171). Oxford University Press, xiv + 487 pp. [164] Dawid, A. P. (2011). Introduction. In Evidence, Inference and Enquiry (Proceedings of the British Academy, vol. 171), edited by A. P. Dawid, W. L. Twining and D. Vasilaki, Chapter 1. Oxford University Press, 1–9. [165] Dawid, A. P., Hepler, A. B. and Schum, D. A. (2011). Inference networks: Bayes and Wigmore. In Evidence, Inference and Enquiry (Proceedings of the British Academy, vol. 171), edited by A. P. Dawid, W. L. Twining and D. Vasilaki, Chapter 5. Oxford University Press, 119–150. [166] Bernardo, J. M., Bayarri, J. M., Berger, J. O., Dawid, A. P., Heckerman, D., Smith, A. F. M. and West, M., Eds. (2011). Bayesian Statistics 9 . Oxford University Press, x + 706 pp. [167] Senn, S., Dawid, A. P., Christie, M. and Cliffe, A., Eds. (2011). Simplicity, Complexity and Mod- elling. J. Wiley and Sons, xiv + 205 pp. DOI:10.1002/9781119951445 [168] Christie, M., Cliffe, A., Dawid, A. P. and Senn, S. (2011). Introduction. In Simplicity, Complexity and Modelling, edited by S. Senn, A. P. Dawid, M. Christie and A. Cliffe, Chapter 1. J. Wiley and Sons, 1–9. DOI:10.1002/9781119951445.ch1 [169] Dawid, A. P. and Senn, S. (2011). Statistical model selection. In Simplicity, Complexity and Mod- elling, edited by S. Senn, A. P. Dawid, M. Christie and A. Cliffe, Chapter 2. J. Wiley and Sons, 11–33. DOI:10.1002/9781119951445.ch2 [170] Christie, M., Cliffe, A., Dawid, A. P. and Senn, S. (2011). Issues for modellers. In Simplicity, Com- plexity and Modelling, edited by S. Senn, A. P. Dawid, M. Christie and A. Cliffe, Chapter 11. J. Wiley and Sons, 187–192. DOI:10.1002/9781119951445.ch11 [171] Parry, M., Dawid, A. P. and Lauritzen, S. L. (2012). Proper local scoring rules. Ann. Statist. 40, 561–592. DOI:10.1214/12-AOS971 Available here [172] Dawid, A. P., Lauritzen, S. L. and Parry, M. (2012). Proper local scoring rules on discrete sample spaces. Ann. Statist. 40, 593–608. DOI:10.1214/12-AOS972 Available here [173] Dawid, A. P. (2012). Invited discussion of ‘Catching up faster by switching sooner: A predictive approach to adaptive estimation with an application to the AIC-BIC dilemma’, by T. van Erven, P. D. Gr¨unwald and S. de Rooij. J. Roy. Statist. Soc.B 74, 397–399. DOI:10.1111/j.1467-9868.2011.01025.x [174] Berzuini, C. R., Dawid, A. P. and Bernardinelli, L., Eds. (2012). Causality: Statistical Perspectives and Applications. John Wiley & Sons, Ltd, Chichester, UK, xxv + 377 pp. DOI:10.1002/9781119945710 [175] Berzuini, C. R., Dawid, A. P. and Bernardinelli, L. (2012). An overview of statistical causality. In Causality: Statistical Perspectives and Applications, edited by C. R. Berzuini, A. P. Dawid and L. Bernardinelli. J. Wiley and Sons, xvii–xxv. DOI:10.1002/9781119945710.fmatter [176] Dawid, A. P. (2012). The decision-theoretic approach to causal inference. In Causality: Statistical Perspectives and Applications, edited by C. R. Berzuini, A. P. Dawid and L. Bernardinelli, Chapter 4. J. Wiley and Sons, 25–42. DOI:10.1002/9781119945710.ch4 [177] Berzuini, C. R,, Dawid, A. P. and Didelez, V. (2012). Assessing dynamic treatment strategies. In Causality: Statistical Perspectives and Applications, edited by C. R. Berzuini, A. P. Dawid and L. Bernardinelli, Chapter 8. J. Wiley and Sons, 85–100. DOI:10.1002/9781119945710.ch8

9 [178] Berzuini, C. R., Dawid, A. P., Zhang, H. and Parkes, M. (2012). Analysis of for identifying causal mechanisms. In Causality: Statistical Perspectives and Applications, edited by C. R. Berzuini, A. P. Dawid and L. Bernardinelli, Chapter 14. J. Wiley and Sons, 192–207. DOI:10.1002/9781119945710.ch14 [179] Dawid, A. P. and Didelez, V. (2012) “Imagine a can opener”—The magic of principal stratum analysis. International Journal of Biostatistics 8 (1). DOI:10.1515/1557-4679.1391 [180] Dawid, A. P. and Musio, M. (2013). Estimation of spatial processes using local scoring rules. AStA Advances in Statistical Analysis 97, 173–179. DOI:10.1007/s10182-012-0191-8 [181] Dawid, A. P. (2013). Invited discussion of ‘A Bayesian approach to complex clinical diagnoses: A case-study in child abuse’, by , Deborah Ashby, Frank Dunstan, David Foreman and Neil McIntosh. J. Roy. Statist. Soc.A 176, 83–84. DOI:10.1111/j.1467-985X.2012.01050.x [182] Berzuini, C. R. and Dawid, A. P. (2013). Deep determinism and the assessment of mechanistic interaction. Biostatistics 14, 502–513. DOI:10.1093/biostatistics/kxs049 [183] Dawid, A. P. (2013). Exchangeability and its ramifications. In Bayesian Theory and Applications, edited by P. Damien, P. Dellaportas, N. G. Polson and D. A. Stephens. Oxford University Press, 19–29. http://ukcatalogue.oup.com/product/9780199695607.do].ULk3A4aa9eM [184] Arrington, L., Leinhardt, Z. M. and Dawid, A. P., Eds. (2013). Beauty. Cambridge University Press, Cambridge, UK, xiv + 195 pp. DOI:10.1017/CBO9781139342421 [185] Musio, M. and Dawid, A. P. (2013). Local scoring rules: A versatile tool for inference. In Proceedings of the 59th ISI World Statistics Congress. International Statistical Institute, 1459–1464. http://2013.isiproceedings.org/Files/STS019-P3-S.pdf [186] Dawid, A. P., Faigman, D. L. and Fienberg, S. E. (2014). Fitting science into legal contexts: Assessing effects of causes or causes of effects? (with Discussion and authors’ rejoinder). Sociological Methods and Research 43, 359–421. DOI:10.1177/0049124113515188 [187] Byrne, S. P. J. and Dawid, A. P. (2014). Retrospective-prospective symmetry in the likelihood and Bayesian analysis of case-control studies. Biometrika 101, 189–204. DOI:10.1093/biomet/ast050 [188] Dawid, A. P. and Musio, M. (2014). Theory and applications of proper scoring rules. Metron 72, 169–183. DOI:10.1007/s40300-014-0039-y [189] Dawid, A. P. (2014). Invited discussion of ‘On the Birnbaum argument for the Strong Likelihood Principle’, by Deborah Mayo. Statistical Science 29, 240–241. DOI:10.1214/14-STS470 [190] Dawid, A. P. and Constantinou, P. (2014). A formal treatment of sequential ignorability. Statistics in Biosciences 6, 166–188. DOI:10.1007/s12561-014-9110-8 [191] Dawid, A. P., Faigman, D. L. and Fienberg, S. E. (2015). On the causes of effects: Response to Pearl. Sociological Methods and Research 44, 165–174. DOI:10.1177/0049124114562613 [192] Dawid, A. P. (2015). Statistical causality from a decision-theoretic perspective. Ann. Rev. Statist. Appl. 2, 273–303. DOI:10.1146/annurev-statistics-010814-020105 e-print [193] Dawid, A. P. and Musio, M. (2015). Bayesian model selection based on proper scoring rules (with Discussion). Bayesian Analysis 10, 479–521. DOI:10.1214/15-BA942

10 [194] Imrey, P. B. and Dawid, A. P. (2015). A commentary on statistical assessment of violence recidivism risk. Statistics and Public Policy 2, 25–42. DOI:10.1080/2330443X.2015.1029338 [195] Byrne, S. P. J. and Dawid, A. P. (2015). Structural Markov graph laws for Bayesian model uncer- tainty. The Annals of Statistics 43, 1647-1681. DOI:10.1214/15-AOS1319 [196] Baio, G. and Dawid, A. P. (2015). Probabilistic sensitivity analysis in health economics. Statistical Methods in Medical Research 24, 615–634. DOI:10.1177/0962280211419832. Epub 2011 Sep 18. [197] Dawid, A. P. (2015). On individual risk. Synthese. Online First, 7 November 2015. DOI:10.1007/s11229-015-0953-4 [198] Dawid, A. P., Musio, M., and Ventura, L. (2016). Minimum scoring rule inference. Scandinavian Journal of Statistics 43, 123–138. DOI:10.1111/sjos.12168 [199] Berzuini, C. R. and Dawid, A. P. (2016). Stochastic mechanistic interaction. Biometrika 103, 89– 102. DOI:10.1093/biomet/asv072 [200] Dawid, A. P. (2016). Invited discussion of ‘Of quantiles and expectiles: Consistent scoring functions, Choquet representations and forecast ,’ by W. Ehm, T. Gneiting, A. Jordan and F. Kr¨uger. J. Roy. Statist. Soc.B 78, 534–5. [201] Dawid, A. P., Musio, M., and Fienberg, S. E. (2016). From statistical evidence to evidence of causality. Bayesian Analysis 11, 725–752. DOI:10.1214/15-BA968 [202] Dawid, A. P., Murtas, R. and Musio, M. (2016). Bounding the probability of causation in mediation analysis. In Topics on Methodological and Applied Statistical Inference, edited by T. Di Battista, E. Moreno and W. Racugno. Springer, 75–84. DOI:10.1007/978-3-319-44093-4. [203] Guo, H., Dawid, A. P. and Berzuini, G. M. (2016). Sufficient covariate, propensity variable and doubly robust estimation. In Statistical Causal Inferences and Their Applications in Public Health Research, edited by Hua He, Pan Wu and Ding-Geng Chen. Springer, 49–89. DOI:10.1007/978-3-319-41259-7 3 [204] Morrison, G. S., Kaye, D. H., Balding, D. J., Taylor, D., Dawid, A. P., Aitken, C. G. G., Gittelson, S., Zadora, G., Robertson, B., Willis, S., Pope, S., Neil, M., Martire, K. A., Hepler, A., Gill, R. D., Jamieson, A., de Zoete, J., Ostrum, R. B. and Caliebe, A. (2016). A comment on the PCAST report: Skip the “match”/“non-match” stage. Forensic Science International (in Press). DOI:10.1016/j.forsciint.2016.10.018 [205] Mortera. J. and Dawid, A. P. (2016). Forensic identification then and now. Statistica Applicata (to appear). [206] Dawid, A. P. (2016). Forensic likelihood ratio: Statistical problems and pitfalls. Science and Justice (to appear). [207] Dawid, A. P. and Mortera. J. Graphical models for forensic analysis. In Handbook of Graphical Models, edited by M. Drton, S. L. Lauritzen, M. Maathuis and M. Wainwright. CRC Press (to appear). [208] Constantinou, P. and Dawid, A. P. (2016). Extended conditional independence and applications in causal inference. Submitted to Annals of Statistics. arXiv:1512.00245 [209] Murtas, R., Dawid, A. P. and Musio, M. (2017). New bounds for the probability of causation in mediation analysis. Submitted to Statistical Methods & Applications.

Some additional Research Reports can be found at: http://tinyurl.com/2maycn/reports.html

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